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    Wyświetlanie 1-57 z 57
    Tytuł:
    Incoherent Dictionary Learning for Sparse Representation in Network Anomaly Detection
    Autorzy:
    Andrysiak, Tomasz
    Saganowski, Łukasz
    Powiązania:
    https://bibliotekanauki.pl/articles/1373708.pdf
    Data publikacji:
    2015
    Wydawca:
    Uniwersytet Jagielloński. Wydawnictwo Uniwersytetu Jagiellońskiego
    Tematy:
    dictionary learning
    sparse representation
    anomaly detection
    Opis:
    In this article we present the use of sparse representation of a signal and incoherent dictionary learning method for the purpose of network traffic analysis. In learning process we use 1D INK-SVD algorithm to detect proper dictionary structure. Anomaly detection is realized by parameter estimation of the analyzed signal and its comparative analysis to network traffic profiles. Efficiency of our method is examined with the use of extended set of test traces from real network traffic. Received experimental results confirm effectiveness of the presented method.
    Źródło:
    Schedae Informaticae; 2015, 24; 63-71
    0860-0295
    2083-8476
    Pojawia się w:
    Schedae Informaticae
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Weak Saturation Numbers for Sparse Graphs
    Autorzy:
    Faudree, Ralph J.
    Gould, Ronald J.
    Jacobson, Michael S.
    Powiązania:
    https://bibliotekanauki.pl/articles/29787240.pdf
    Data publikacji:
    2013-09-01
    Wydawca:
    Uniwersytet Zielonogórski. Wydział Matematyki, Informatyki i Ekonometrii
    Tematy:
    saturated graphs
    sparse graphs
    weak saturation
    Opis:
    For a fixed graph F, a graph G is F-saturated if there is no copy of F in G, but for any edge e ∉ G, there is a copy of F in G + e. The minimum number of edges in an F-saturated graph of order n will be denoted by sat(n, F). A graph G is weakly F-saturated if there is an ordering of the missing edges of G so that if they are added one at a time, each edge added creates a new copy of F. The minimum size of a weakly F-saturated graph G of order n will be denoted by wsat(n, F). The graphs of order n that are weakly F-saturated will be denoted by wSAT(n, F), and those graphs in wSAT(n, F) with wsat(n, F) edges will be denoted by wSAT(n, F). The precise value of wsat(n, T) for many families of sparse graphs, and in particular for many trees, will be determined. More specifically, families of trees for which wsat(n, T) = |T|−2 will be determined. The maximum and minimum values of wsat(n, T) for the class of all trees will be given. Some properties of wsat(n, T) and wSAT(n, T) for trees will be discussed. Keywords: saturated graphs, sparse graphs, weak saturation.
    Źródło:
    Discussiones Mathematicae Graph Theory; 2013, 33, 4; 677-693
    2083-5892
    Pojawia się w:
    Discussiones Mathematicae Graph Theory
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A fault detection method based on stacking the SAE-SRBM for nonstationary and stationary hybrid processes
    Autorzy:
    Huang, Lei
    Ren, Hao
    Chai, Yi
    Qu, Jianfeng
    Powiązania:
    https://bibliotekanauki.pl/articles/1838177.pdf
    Data publikacji:
    2021
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    fault detection
    sparse autoencoder
    sparse restricted Boltzmann machine
    hybrid industrial processes
    detekcja błędów
    autoenkoder
    proces przemysłowy
    Opis:
    This paper proposes a fault detection method by extracting nonlinear features for nonstationary and stationary hybrid industrial processes. The method is mainly built on the basis of a sparse auto-encoder and a sparse restricted Boltzmann machine (SAE-SRBM), so as to take advantages of their adaptive extraction and fusion on strong nonlinear symptoms. In the present work, SAEs are employed to reconstruct inputs and accomplish feature extraction by unsupervised mode, and their outputs present a knotty problem of an unknown probability distribution. In order to solve it, SRBMs are naturally used to fuse these unknown probability distribution features by transforming them into energy characteristics. The contribution of this method is the capability of further mining and learning of nonlinear features without considering the nonstationary problem. Also, this paper introduces a method of constructing labeled and unlabeled training samples while maintaining time series features. Unlabeled samples can be adopted to train the part for feature extraction and fusion, while labeled samples can be used to train the classification part. Finally, a simulation on the Tennessee Eastman process is carried out to demonstrate the effectiveness and excellent performance on fault detection for nonstationary and stationary hybrid industrial processes.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2021, 31, 1; 29-43
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Recognition of the numbers in the Polish language
    Autorzy:
    Plichta, A.
    Gąciarz, T.
    Krzywdziński, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/308844.pdf
    Data publikacji:
    2013
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    Automatic Speech Recognition
    compressed sensing
    Sparse Classification
    Opis:
    Automatic Speech Recognition is one of the hottest research and application problems in today’s ICT technologies. Huge progress in the development of the intelligent mobile systems needs an implementation of the new services, where users can communicate with devices by sending audio commands. Those systems must be additionally integrated with the highly distributed infrastructures such as computational and mobile clouds, Wireless Sensor Networks (WSNs), and many others. This paper presents the recent research results for the recognition of the separate words and words in short contexts (limited to the numbers) articulated in the Polish language. Compressed Sensing Theory (CST) is applied for the first time as a methodology of speech recognition. The effectiveness of the proposed methodology is justified in numerical tests for both separate words and short sentences.
    Źródło:
    Journal of Telecommunications and Information Technology; 2013, 4; 70-78
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Efektywna metoda przetwarzania macierzy rzadkich
    Effective method of processing of sparse matrix
    Autorzy:
    Jabłoński, J.
    Turos, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/152889.pdf
    Data publikacji:
    2007
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    kompresja
    macierze rzadkie
    compression
    sparse matrix
    Opis:
    Wiele problemów optymalizacyjnych sprowadzanych jest do przetwarzania macierzy rzadkich o bardzo dużych rozmiarach. Tradycyjne metody operacji na macierzach o tak dużych rozmiarach jest czasochłonne dlatego poszukiwane są rozwiązania gwarantujące większą efektywność i krótszy czas przetwarzania. W artykule omówiono wybrane metody i zaproponowano autorską metodę wykorzystania kompresji w poprawie efektywności przetwarzania macierzy rzadkich.
    Many optimization problems can be imported to processing of thin matrices about very large sizes. The traditional methods of operation on the matrices about so it is the large sizes time-consuming therefore the guaranteeing the larger efficiency solutions be in the demand and the shorter time of processing. This paper presented the author's method of utilization in improvement of efficiency the compression of processing of sparse matrix in presented study was introduced.
    Źródło:
    Pomiary Automatyka Kontrola; 2007, R. 53, nr 5, 5; 63-65
    0032-4140
    Pojawia się w:
    Pomiary Automatyka Kontrola
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A fault detection method based on stacking the SAE-SRBM for nonstationary and stationary hybrid processes
    Autorzy:
    Huang, Lei
    Ren, Hao
    Chai, Yi
    Qu, Jianfeng
    Powiązania:
    https://bibliotekanauki.pl/articles/1838184.pdf
    Data publikacji:
    2021
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    fault detection
    sparse autoencoder
    sparse restricted Boltzmann machine
    hybrid industrial processes
    detekcja błędu
    autoenkoder
    proces przemysłowy
    Opis:
    This paper proposes a fault detection method by extracting nonlinear features for nonstationary and stationary hybrid industrial processes. The method is mainly built on the basis of a sparse auto-encoder and a sparse restricted Boltzmann machine (SAE-SRBM), so as to take advantages of their adaptive extraction and fusion on strong nonlinear symptoms. In the present work, SAEs are employed to reconstruct inputs and accomplish feature extraction by unsupervised mode, and their outputs present a knotty problem of an unknown probability distribution. In order to solve it, SRBMs are naturally used to fuse these unknown probability distribution features by transforming them into energy characteristics. The contribution of this method is the capability of further mining and learning of nonlinear features without considering the nonstationary problem. Also, this paper introduces a method of constructing labeled and unlabeled training samples while maintaining time series features. Unlabeled samples can be adopted to train the part for feature extraction and fusion, while labeled samples can be used to train the classification part. Finally, a simulation on the Tennessee Eastman process is carried out to demonstrate the effectiveness and excellent performance on fault detection for nonstationary and stationary hybrid industrial processes.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2021, 31, 1; 29-43
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The versatile hardware accelerator framework for sparse vector calculations
    Autorzy:
    Karwatowski, R.
    Wiatr, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/114705.pdf
    Data publikacji:
    2015
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    FPGA
    sparse vectors
    cosine similarity
    Zynq
    hardware accelerator
    Opis:
    In this paper, we present the advantage of the ability of FPGAs to perform various computationally complex calculations using deep pipelining and parallelism. We propose an architecture that consists of many small stream processing blocks. The designed framework maintains proper data movement and synchronization. The architecture can be easily adapted to be implemented in FPGA devices of a various size and cost - from small SoC devices to high-end PCIe accelerator cards. It is capable to perform a selected operation on a sparse data that are loaded as the stream of vectors. As an example application, we have implemented the cosine similarity measure for the text similarity calculations that uses the TF-IDF weighting scheme. The presented example application calculates the similarity of texts from the set of input documents to documents from the large database. The scheme is used to find the most similar documents. The proposed design can decrease the service time of search queries in computer centers while reducing power consumption.
    Źródło:
    Measurement Automation Monitoring; 2015, 61, 7; 327-329
    2450-2855
    Pojawia się w:
    Measurement Automation Monitoring
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Asymmetric double image encryption, compression and watermarking scheme based on orthogonal-triangular decomposition with column pivoting
    Autorzy:
    Anjana, Savita
    Rakheja, Pankaj
    Yadav, Ak
    Singh, Phool
    Singh, Hukum
    Powiązania:
    https://bibliotekanauki.pl/articles/2086764.pdf
    Data publikacji:
    2022
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    QR decomposition
    Fresnel transform
    sparse matrix
    asymmetric cryptosystem
    Opis:
    A novel asymmetric scheme for double image encryption, compression and watermarking based on QR decomposition in the Fresnel domain has been presented. The QR decomposition provides a permutation matrix as a ciphertext, and the product of orthogonal and triangular matrix as a key. The ciphertext obtained through this process is a sparse matrix that is compressed by the CSR method to give compressed encrypted data, which when combined with a host image, gives a watermarked image. Thus, a cryptosystem that involves compression and watermarking is proposed. The proposed scheme is validated for grayscale images. To check the efficacy of the proposed scheme, histograms, statistical parameters, and key sensitivity are analyzed. The scheme is also tested against various attacks. Numerical simulations are performed to validate the security of the scheme.
    Źródło:
    Optica Applicata; 2022, 52, 2; 283--295
    0078-5466
    1899-7015
    Pojawia się w:
    Optica Applicata
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Równoległa implementacja metod iteracyjnych dla układu równań z macierzami rzadkimi
    Parallel implementation of iterative methods for sparse linear systems
    Autorzy:
    Schubring, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/250420.pdf
    Data publikacji:
    2013
    Wydawca:
    Instytut Naukowo-Wydawniczy TTS
    Tematy:
    metoda iteracyjna
    macierze rzadkie
    UPC
    iterative method
    sparse matrix
    Opis:
    W artykule podano równoległą implementację metod rozwiązywania układu równań liniowych z macierzą rzadką w języku programowania UPC (Unified Parallel C). Uwzględniono możliwości środowiska programistycznego Berkeley UPC oraz format spakowanych wierszy CSR (Compressed Sparse Row).
    Paper described a parallel implementation of the iterative methods for solving linear equation systems with sparse matrix in the UPC programming language (Unified Parallel C). Possibilities of the Berkeley UPC development environment and the CSR packed rows format (Compressed Sparse Row) were included.
    Źródło:
    TTS Technika Transportu Szynowego; 2013, 10; 499-505, CD
    1232-3829
    2543-5728
    Pojawia się w:
    TTS Technika Transportu Szynowego
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    High-resolution Direction of Arrival Estimation Method Based on Sparse Arrays with Minimum Number of Elements
    Autorzy:
    Mohammed, Jafar Ramadhan
    Powiązania:
    https://bibliotekanauki.pl/articles/1839475.pdf
    Data publikacji:
    2021
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    compressed sensing
    direction of arrival
    DOA
    estimation
    sparse array
    Opis:
    Regular fully filled antenna arrays have been widely used in direction of arrival (DOA) estimation. However, practical implementation of these arrays is rather complex and their resolutions are limited to the beamwidth of the array pattern. Therefore, higher resolution and simpler methods are desirable. In this paper, the compressed sensing method is first applied to an initial fully filled array to randomly select the most prominent and effective elements which are used to form the sparse array. To keep the dimension of the sparse array equal to that of the fully filled array, the first and the last elements were excluded from the sparseness process. In addition, some constraints on the sparse spectrum are applied to increase estimation accuracy. The optimization problem is then solved iteratively using the iterative reweighted l1 norm. Finally, a simple searching algorithm is used to detect peaks in the spectrum solution that correspond to the directions of the arriving signals. Compared with the existing scanned beam methods, such as the minimum variance distortionless response (MVDR) technique, and with subspace approaches, such as multiple signal classification (MUSIC) and ESPIRT algorithms, the proposed sparse array method offers better performance even with a lower number of array elements and in severely noisy environments. Effectiveness of the proposed sparse array method is verified via computer simulations.
    Źródło:
    Journal of Telecommunications and Information Technology; 2021, 1; 8-14
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    High-resolution Direction of Arrival Estimation Method Based on Sparse Arrays with Minimum Number of Elements
    Autorzy:
    Mohammed, Jafar Ramadhan
    Powiązania:
    https://bibliotekanauki.pl/articles/1839489.pdf
    Data publikacji:
    2021
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    compressed sensing
    direction of arrival
    DOA
    estimation
    sparse array
    Opis:
    Regular fully filled antenna arrays have been widely used in direction of arrival (DOA) estimation. However, practical implementation of these arrays is rather complex and their resolutions are limited to the beamwidth of the array pattern. Therefore, higher resolution and simpler methods are desirable. In this paper, the compressed sensing method is first applied to an initial fully filled array to randomly select the most prominent and effective elements which are used to form the sparse array. To keep the dimension of the sparse array equal to that of the fully filled array, the first and the last elements were excluded from the sparseness process. In addition, some constraints on the sparse spectrum are applied to increase estimation accuracy. The optimization problem is then solved iteratively using the iterative reweighted l1 norm. Finally, a simple searching algorithm is used to detect peaks in the spectrum solution that correspond to the directions of the arriving signals. Compared with the existing scanned beam methods, such as the minimum variance distortionless response (MVDR) technique, and with subspace approaches, such as multiple signal classification (MUSIC) and ESPIRT algorithms, the proposed sparse array method offers better performance even with a lower number of array elements and in severely noisy environments. Effectiveness of the proposed sparse array method is verified via computer simulations.
    Źródło:
    Journal of Telecommunications and Information Technology; 2021, 1; 8-14
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Pre-trained deep neural network using sparse autoencoders and scattering wavelet transform for musical genre recognition
    Autorzy:
    Kleć, M.
    Korzinek, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/952940.pdf
    Data publikacji:
    2015
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    Sparse Autoencoders
    deep learning
    genre recognition
    Scattering Wavelet Transform
    Opis:
    Research described in this paper tries to combine the approach of Deep Neural Networks (DNN) with the novel audio features extracted using the Scatter- Ing Wavelet Transform (SWT) for classifying musical genres. The SWT uses A sequence of Wavelet Transforms to compute the modulation spectrum coef- Ficients of multiple orders, which has already shown to be promising for this Task. The DNN in this work uses pre-trained layers using Sparse Autoencoders (SAE). Data obtained from the Creative Commons website jamendo.com is Used to boost the well-known GTZAN database, which is a standard bench- mark for this task. The final classifier is tested using a 10-fold cross validation To achieve results similar to other state-of-the-art approaches.
    Źródło:
    Computer Science; 2015, 16 (2); 133-144
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Effects of Sparse Initialization in Deep Belief Networks
    Autorzy:
    Grzegorczyk, K.
    Kurdziel, M.
    Wójcik, P. I.
    Powiązania:
    https://bibliotekanauki.pl/articles/305264.pdf
    Data publikacji:
    2015
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    sparse initialization
    Deep Belief Networks
    Noisy Rectified Linear Units
    Opis:
    Deep neural networks are often trained in two phases: first, hidden layers are pretrained in an unsupervised manner, and then the network is fine-tuned with error backpropagation. Pretraining is often carried out using Deep Belief Networks (DBNs), with initial weights set to small random values. However, recent results established that well-designed initialization schemes, e.g., Sparse Initialization (SI), can greatly improve the performance of networks that do not use pretraining. An interesting question arising from these results is whether such initialization techniques wouldn’t also improve pretrained networks. To shed light on this question, in this work we evaluate SI in DBNs that are used to pretrain discriminative networks. The motivation behind this research is our observation that SI has an impact on the features learned by a DBN during pretraining. Our results demonstrate that this improves network performance: when pretraining starts from sparsely initialized weight matrices, networks achieve lower classification errors after fine-tuning.
    Źródło:
    Computer Science; 2015, 16 (4); 313-327
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Real-time motion tracking using optical flow on multiple GPUs
    Autorzy:
    Mahmoudi, S. A.
    Kierzynka, M.
    Manneback, P.
    Kurowski, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/200476.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Lucas-Kanade method
    sparse optical flow
    multiple GPU computations
    Opis:
    Motion tracking algorithms are widely used in computer vision related research. However, the new video standards, especially those in high resolutions, cause that current implementations, even running on modern hardware, no longer meet the needs of real-time processing. To overcome this challenge several GPU (Graphics Processing Unit) computing approaches have recently been proposed. Although they present a great potential of a GPU platform, hardly any is able to process high definition video sequences efficiently. Thus, a need arose to develop a tool being able to address the outlined problem. In this paper we present software that implements optical flow motion tracking using the Lucas-Kanade algorithm. It is also integrated with the Harris corner detector and therefore the algorithm may perform sparse tracking, i.e. tracking of the meaningful pixels only. This allows to substantially lower the computational burden of the method. Moreover, both parts of the algorithm, i.e. corner selection and tracking, are implemented on GPU and, as a result, the software is immensely fast, allowing for real-time motion tracking on videos in Full HD or even 4K format. In order to deliver the highest performance, it also supports multiple GPU systems, where it scales up very well.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2014, 62, 1; 139-150
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Application of sparse linear discriminant analysis for prediction of protein-protein interactions
    Autorzy:
    Stąpor, K.
    Fabian, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/95137.pdf
    Data publikacji:
    2016
    Wydawca:
    Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
    Tematy:
    sparse discriminant analysis
    feature selection
    protein-protein interaction
    Opis:
    To understand the complex cellular mechanisms involved in a biological system, it is necessary to study protein-protein interactions (PPIs) at the molecular level, in which prediction of PPIs plays a significant role. In this paper we propose a new classification approach based on the sparse discriminant analysis [10] to predict obligate (permanent) and non-obligate (transient) protein-protein interactions. The sparse discriminant analysis [10] circumvents the limitations of the classical discriminant analysis [4, 9] in the high dimensional low sample size settings by incorporating inherently the feature selection into the optimization procedure. To characterize properties of protein interaction, we proposed to use the binding free energies. The performance of our proposed classifier is 75% ± 5%.
    Źródło:
    Information Systems in Management; 2016, 5, 1; 109-118
    2084-5537
    2544-1728
    Pojawia się w:
    Information Systems in Management
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Single Image Super-Resolution through Sparse Representation via Coupled Dictionary learning
    Autorzy:
    Patel, Rutul
    Thakar, Vishvjit
    Joshi, Rutvij
    Powiązania:
    https://bibliotekanauki.pl/articles/226607.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    single image super-resolution
    Dictionary Learning
    Sparse representation
    Opis:
    Single Image Super-Resolution (SISR) through sparse representation has received much attention in the past decade due to significant development in sparse coding algorithms. However, recovering high-frequency textures is a major bottleneck of existing SISR algorithms. Considering this, dictionary learning approaches are to be utilized to extract high-frequency textures which improve SISR performance significantly. In this paper, we have proposed the SISR algorithm through sparse representation which involves learning of Low Resolution (LR) and High Resolution (HR) dictionaries simultaneously from the training set. The idea of training coupled dictionaries preserves correlation between HR and LR patches to enhance the Super-resolved image. To demonstrate the effectiveness of the proposed algorithm, a visual comparison is made with popular SISR algorithms and also quantified through quality metrics. The proposed algorithm outperforms compared to existing SISR algorithms qualitatively and quantitatively as shown in experimental results. Furthermore, the performance of our algorithm is remarkable for a smaller training set which involves lesser computational complexity. Therefore, the proposed approach is proven to be superior based upon visual comparisons and quality metrics and have noticeable results at reduced computational complexity.
    Źródło:
    International Journal of Electronics and Telecommunications; 2020, 66, 2; 347-353
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    CG-SCMA Codebook Design Based on Maximized Euclidian Distance
    Autorzy:
    Mohamed, Sura S.
    Abdullah, Hikmat N.
    Powiązania:
    https://bibliotekanauki.pl/articles/2200958.pdf
    Data publikacji:
    2023
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    codebook
    Euclidian distance
    MPA
    multiple access
    sparse code
    Opis:
    Sparse code multiple access (SCMA) is a multi-dimensional codebook based on a class of non-orthogonal multiple access (NOMA) technologies enabling the delivery of non-orthogonal resource elements to numerous users in 5G wireless communications without increasing complexity. This paper proposes a computer-generated sparse code multiple access (CG-SCMA) technique, where the minimum Euclidian distance (MED) of a star 16-point quadrature amplitude modulation is maximized by CG-SCMA, thus creating a complex SCMA codebook based on optimizing the difference between the first and other radiuses over rotated constellations. To specify the most suitable values for this constellation, it is divided into four sub-constellations using trellis coded modulation (TCM) in an effort to optimize MED. The new codebook has four sub-constellations with MED values of 3.85, 2.26, 2.26, and 3.85, respectively. Application of the message passing algorithm (MPA) ensures low complexity of the decoding process
    Źródło:
    Journal of Telecommunications and Information Technology; 2023, 1; 18--24
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Blind Estimation of Linear and Nonlinear Sparse Channels
    Autorzy:
    Georgoulakis, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/307846.pdf
    Data publikacji:
    2013
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    blind estimation and equalization
    clustering techniques
    sparse zero pad channels
    Opis:
    This paper presents a Clustering Based Blind Channel Estimator for a special case of sparse channels - the zero pad channels. The proposed algorithm uses an unsupervised clustering technique for the estimation of data clusters. Clusters labelling is performed by a Hidden Markov Model of the observation sequence appropriately modified to exploit channel sparsity. The algorithm achieves a substantial complexity reduction compared to the fully evaluated technique. The proposed algorithm is used in conjunction with a Parallel Trellis Viterbi Algorithm for data detection and simulation results show that the overall scheme exhibits the reduced complexity benefits without performance reduction.
    Źródło:
    Journal of Telecommunications and Information Technology; 2013, 1; 65-71
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Evaluating four remote sensing based models to estimate latent heat flux in semi-arid climate for heterogeneous surface coverage of western Algeria
    Autorzy:
    Oualid, Tewfik A.
    Hamimed, Abderahmane
    Khaldi, Abdelkader
    Powiązania:
    https://bibliotekanauki.pl/articles/2174320.pdf
    Data publikacji:
    2022
    Wydawca:
    Instytut Technologiczno-Przyrodniczy
    Tematy:
    Algeria
    energy balance
    evapotranspiration
    Landsat
    METRIC
    SPARSE
    TIM
    TSEB
    Opis:
    Optimal estimation of water balance components at the local and regional scales is essential for many applications such as integrated water resources management, hydrogeological modelling and irrigation scheduling. Evapotranspiration is a very important component of the hydrological cycle at the soil surface, particularly in arid and semi-arid lands. Mapping evapotranspiration at high resolution with internalised calibration (METRIC), trapezoid interpolation model (TIM), two-source energy balance (TSEB), and soil-plant-atmosphere and remote sensing evapotranspiration (SPARSE) models were applied using Landsat 8 images for four dates during 2014-2015 and meteorological data. Surface energy maps were then generated. Latent heat flux estimated by four models was then compared and evaluated with those measured by applying the method of Bowen ratio for the various days. In warm periods with high water stress differences and with important surface temperature differences, METRIC proves to be the most robust with the root-mean-square error (RMSE) less than 40 W∙m-2. However, during the periods with no significant surface temperature and soil humidity differences, SPARSE model is superior with the RMSE of 35 W∙m-2. The results of TIM are close to METRIC, since both models are sensitive to the difference in surface temperature. However, SPARSE remains reliable with the RMSE of 55 W∙m-2 unlike TSEB, which has a large deviation from the other models. On the other hand, during the days when the temperature difference is small, SPARSE and TSEB are superior, with a clear advantage of SPARSE serial version, where temperature differences are less important.
    Źródło:
    Journal of Water and Land Development; 2022, 55; 259--275
    1429-7426
    2083-4535
    Pojawia się w:
    Journal of Water and Land Development
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Speech Enhancement Based on Constrained Low-rank Sparse Matrix Decomposition Integrated with Temporal Continuity Regularisation
    Autorzy:
    Sun, Chengli
    Yuan, Conglin
    Powiązania:
    https://bibliotekanauki.pl/articles/178075.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    speech enhancement
    temporal continuity
    low-rank decomposition
    sparse decomposition
    Opis:
    Speech enhancement in strong noise condition is a challenging problem. Low-rank and sparse matrix decomposition (LSMD) theory has been applied to speech enhancement recently and good performance was obtained. Existing LSMD algorithms consider each frame as an individual observation. However, real-world speeches usually have a temporal structure, and their acoustic characteristics vary slowly as a function of time. In this paper, we propose a temporal continuity constrained low-rank sparse matrix decomposition (TCCLSMD) based speech enhancement method. In this method, speech separation is formulated as a TCCLSMD problem and temporal continuity constraints are imposed in the LSMD process. We develop an alternative optimisation algorithm for noisy spectrogram decomposition. By means of TCCLSMD, the recovery speech spectrogram is more consistent with the structure of the clean speech spectrogram, and it can lead to more stable and reasonable results than the existing LSMD algorithm. Experiments with various types of noises show the proposed algorithm can achieve a better performance than traditional speech enhancement algorithms, in terms of yielding less residual noise and lower speech distortion.
    Źródło:
    Archives of Acoustics; 2019, 44, 4; 681-692
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Error Analysis of Sound Source Directivity Interpolation Based on Spherical Harmonics
    Autorzy:
    Szwajcowski, Adam
    Krause, Daniel
    Snakowska, Anna
    Powiązania:
    https://bibliotekanauki.pl/articles/1953503.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    sound source directivity
    spherical harmonics
    interpolation error
    sparse measurements
    Opis:
    Precise measurement of the sound source directivity not only requires special equipment, but also is time-consuming. Alternatively, one can reduce the number of measurement points and apply spatial interpolation to retrieve a high-resolution approximation of directivity function. This paper discusses the interpolation error for different algorithms with emphasis on the one based on spherical harmonics. The analysis is performed on raw directivity data for two loudspeaker systems. The directivity was measured using sampling schemes of different densities and point distributions (equiangular and equiareal). Then, the results were interpolated and compared with these obtained on the standard 5° regular grid. The application of the spherical harmonic approximation to sparse measurement data yields a mean error of less than 1 dB with the number of measurement points being reduced by 89%. The impact of the sparse grid type on the retrieval error is also discussed. The presented results facilitate optimal sampling grid choice for low-resolution directivity measurements.
    Źródło:
    Archives of Acoustics; 2021, 46, 1; 95-104
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Parallel Algorithms for Forward and Back Substitution in Linear Algebraic Equations of Finite Element Method
    Autorzy:
    Fialko, Sergiy
    Powiązania:
    https://bibliotekanauki.pl/articles/308616.pdf
    Data publikacji:
    2019
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    finite element method
    multithreaded parallelization
    sparse symmetric matrices
    triangular solution
    Opis:
    This paper considers several algorithms for parallelizing the procedure of forward and back substitution for high-order symmetric sparse matrices on multi-core computers with shared memory. It compares the proposed approaches for various finite-element problems of structural mechanics which generate sparse matrices of different structures.
    Źródło:
    Journal of Telecommunications and Information Technology; 2019, 4; 20-29
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Semantic Sparse Representation of Disease Patterns
    Autorzy:
    Przelaskowski, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/226810.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    sparse representation
    compressive sensing
    information theory
    semantic information
    disease pattern
    Opis:
    Sparse data representation is discussed in a context of useful fundamentals led to semantic content description and extraction of information. Disease patterns as semantic information extracted from medical images were underlined because of discussed application of computer-aided diagnosis. Compressive sensing rules were adjusted to the requirements of diagnostic pattern recognition. Proposed methodology of sparse disease patterns considers accuracy of sparse representation to estimate target content for detailed analysis. Semantics of sparse representation were modeled by morphological content analysis. Subtle or hidden components were extracted and displayed to increase information completeness. Usefulness of sparsity was verified for computer-aided diagnosis of stroke based on brain CT scans. Implemented method was based on selective and sparse representation of subtle hypodensity to improve diagnosis. Visual expression of disease signatures was fixed to radiologist requirements, domain knowledge and experimental analysis issues. Diagnosis assistance suitability was proven by experimental subjective rating and automatic recognition.
    Źródło:
    International Journal of Electronics and Telecommunications; 2010, 56, 3; 273-280
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Design Low Complexity SCMA Codebook Using Arnold’s Cat Map
    Autorzy:
    Mohamed, Sura S.
    Abdullah, Hikmat N.
    Powiązania:
    https://bibliotekanauki.pl/articles/2174447.pdf
    Data publikacji:
    2022
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    chaotic interleaving
    codebook design
    dimension rotation
    Euclidean distance
    sparse code multiple access
    Opis:
    In 5G wireless communications, sparse code multiple access (SCMA) – a multi-dimensional codebook based on a specific category of the non-orthogonal multiple access (NOMA) technique - enables many users to share non-orthogonal resource components with a low level of detection complexity. The multi-dimensional SCMA (MD-SCMA) codebook design presented in this study is based on the constellation rotation and interleaving method. Initially, a subset of the lattice Z 2 is used to form the mother constellation’s initial dimension. The first dimension is then rotated to produce other dimensions. Additionally, interleaving is employed for even dimensions to enhance fading channel performance. Arnold’s chaotic cat map is proposed as the interleaving method to reduce computational complexity. Performance of the SCMA codebook based on interleaving is evaluated by comparing it with selected codebooks for SCMA multiplexing. The metrics used for performance evaluation purposes include bit error rate (BER), peak to average power ratio (PAPR), and minimum Euclidean distance (MED), as well as complexity. The results demonstrate that the suggested codebook with chaotic interleaving offers performance that is equivalent to that of the conventional codebook based on interleaving. It is characterized by lower MED and higher BER compared to computer-generated and 16-star QAM codebook design approaches, but its complexity is lower than that of the conventional codebook based on interleaving.
    Źródło:
    Journal of Telecommunications and Information Technology; 2022, 4; 13--20
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Computational aspects of GPU - accelerated sparse matrix - vector multiplication for solving Markov models
    Obliczeniowe aspekty mnożenia macierzy rzadkiej przez wektor dla rozwiązywania modeli Markowa przyspieszanego przez karty GPU
    Autorzy:
    Bylina, B.
    Bylina, J.
    Karwacki, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/375696.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Markovian models
    wireless network models
    GPU
    matrix-vector multiplication
    sparse matrices
    Opis:
    In this article we investigate some computational aspects of GPU-accelerated matrix-vector multiplication where matrix is sparse. Particularly, we deal with sparse matrices appearing in modelling with Markovian queuing models. The model we use for research is a Markovian queuing model of a wireless device. This model describes the device’s behavior during possible channel occupation by other devices. We study the efficiency of multiplication of a sparse matrix by a dense vector with the use of an appropriate, ready-to-use GPU-accelerated mathematical library, namely CUSP. For the CUSP library we discuss data structures and their impact on the CUDA platform for the fine-grained parallel architecture of the GPU. Our aim is to find the best format for storing a sparse matrix for GPU-computation (especially one associated with the Markovian model of a wireless device). We compare the time, the performance and the speed-up for the card NVIDIA Tesla C2050 (with ECC ON). For unstructured matrices (as our Markovian matrices), we observe speed-ups (in respect to CPU-only computations) of over 8 times.
    Łańcuchy Markowa są przydatnym narzędziem do modelowania systemów złożonych, takich jak systemy i sieci komputerowe. W ostatnich latach łańcuchy Markowa zostały z powodzeniem wykorzystane do oceny pracy sieci bezprzewodowych. Jednym z problemów jaki się pojawia przy wykorzystywaniu łańcuchów Markowa w modelowaniu sieci są problemy natury obliczeniowej. W artykule zajmiemy się badaniem mnożenia macierzy rzadkiej przez wektor, które jest jedną z głównych operacji podczas numerycznego rozwiązywania modeli Markowowskich. Aby, przyspieszyć czas obliczeń mnożenia macierz rzadkiej przez wektor wykorzystano funkcje z biblioteki CUSP. Biblioteka jest zbiorem funkcji wykonywanych na GPU (ang.Graphics Processing Unit) celem skrócenia czasu obliczeń. Do testowania operacji mnożenia macierzy rzadkiej przez wektor badano macierze z Markowowskiego modelu pracy sieci bezprzewodowej. Model ten opisuje zachowanie urządzenia, gdy kanał transmisyjnych może być zajęty przez inne urządzenia. Macierz przejść wspomnianego modelu jest macierzą rzadką i potrzeba specialnej struktury danych do jej przechowywania, dlatego w artykule dyskutowane są różne struktury danych dla macierzy rzadkich i ich przydatność do obliczen na kartach graficznych. W pracy porównano czas, wydajność i przyspieszenie jakie otrzymano podczas testowania biblioteki CUSP na karcie NVIDIA Tesla C2050 dla niestrukturalnych macierzy rzadkich opisujących model zajętości węzła w sieciach bezprzewodowych przy różnych formatach przechowywania macierzy rzadkich. Dla testowanych macierzy zauważono ośmiokrotne przyspieszenie obliczeń przy wykorzystaniu karty graficznej.
    Źródło:
    Theoretical and Applied Informatics; 2011, 23, 2; 127-145
    1896-5334
    Pojawia się w:
    Theoretical and Applied Informatics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Underwater target direction of arrival estimation by small acoustic sensor array based on sparse bayesian learning
    Autorzy:
    Wang, B.
    He, C.
    Powiązania:
    https://bibliotekanauki.pl/articles/260588.pdf
    Data publikacji:
    2017
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    DOA
    underwater acoustic signal processing
    sparse Bayesian learning
    temporally correlated source
    Opis:
    Assuming independently but identically distributed sources, the traditional DOA (direction of arrival) estimation method of underwater acoustic target normally has poor estimation performance and provides inaccurate estimation results. To solve this problem, a new high-accuracy DOA algorithm based on sparse Bayesian learning algorithm is proposed in terms of temporally correlated source vectors. In novel method, we regarded underwater acoustic source as a first-order auto-regressive process. And then we used the new algorithm of multi-vector SBL to reconstruct the signal spatial spectrum. Then we used the CS-MMV model to estimate the DOA. The experiment results have shown the novel algorithm has a higher spatial resolution and estimation accuracy than other DOA algorithms in the cases of less array element space and less snapshots.
    Źródło:
    Polish Maritime Research; 2017, S 2; 95-102
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Design of Sparse FIR Filters with Low Group Delay
    Autorzy:
    Konopacki, Jacek
    Powiązania:
    https://bibliotekanauki.pl/articles/1844604.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    digital filters
    FIR filter design
    sparse filters
    reduced group delay filters
    Opis:
    The aim of the work is to present the method for designing sparse FIR filters with very low group delay and approximately linear-phase in the passband. Significant reduction of the group delay, e.g. several times in relation to the linear phase filter, may cause the occurrence of undesirable overshoot in the magnitude frequency response. The method proposed in this work consists of two stages. In the first stage, FIR filter with low group delay is designed using minimax constrained optimization that provides overshoot elimination. In the second stage, the same process is applied iteratively to reach sparse solution. Design examples demonstrate the effectiveness of the proposed method.
    Źródło:
    International Journal of Electronics and Telecommunications; 2021, 67, 1; 121-126
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Frequency Selection Based Separation of Speech Signals with Reduced Computational Time Using Sparse NMF
    Autorzy:
    Varshney, Y. V.
    Abbasi, Z. A.
    Abidi, M. R.
    Farooq, O.
    Powiązania:
    https://bibliotekanauki.pl/articles/176829.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    sparse NMF
    non-negative matrix factorisation
    mixed speech recognition
    machine learning
    Opis:
    Application of wavelet decomposition is described to speed up the mixed speech signal separation with the help of non-negative matrix factorisation (NMF). It is assumed that the basis vectors of training data of individual speakers had been recorded. In this paper, the spectrogram magnitude of a mixed signal has been factorised with the help of NMF with consideration of sparseness of speech signals. The high frequency components of signal contain very small amount of signal energy. By rejecting the high frequency components, the size of input signal is reduced, which reduces the computational time of matrix factorisation. The signal of lower energy has been separated by using wavelet decomposition. The present work is done for wideband microphone speech signal and standard audio signal from digital video equipment. This shows an improvement in the separation capability using the proposed model as compared with an existing one in terms of correlation between separated and original signals. Obtained signal to distortion ratio (SDR) and signal to interference ratio (SIR) are also larger as compare of the existing model. The proposed model also shows a reduction in computational time, which results in faster operation.
    Źródło:
    Archives of Acoustics; 2017, 42, 2; 287-295
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Local Characterisation and Detection of Woven Fabric Texture Based on a Sparse Dictionary
    Autorzy:
    Wu, Ying
    Wang, Ren
    Lou, Lin
    Wang, Lali
    Wang, Jun
    Powiązania:
    https://bibliotekanauki.pl/articles/2172000.pdf
    Data publikacji:
    2022
    Wydawca:
    Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
    Tematy:
    fabric texture representation
    sparse representation
    weave repeat
    defect detection
    dictionary learning
    Opis:
    To achieve enhanced accuracy of fabric representation and defect detection, an innovative approach using a sparse dictionary with small patches was used for fabric texture characterisation. The effectiveness of the algorithm proposed was tested through comprehensive characterisation by studying eight weave patterns: plain, twill, weft satin, warp satin, basket, honeycomb, compound twill, and diamond twill and detecting fabric defects. Firstly, the main parameters such as dictionary size, patch size, and cardinality T were optimised, and then 40 defect-free fabric samples were characterised by the algorithm proposed. Subsequently, the Impact of the weave pattern was investigated based on the representation result and texture structure. Finally, defective fabrics were detected. The algorithm proposed is an alternative simple and scalable method to characterise fabric texture and detect textile defects in a single step without extracting features or prior information.
    Źródło:
    Fibres & Textiles in Eastern Europe; 2022, 3 (151); 33--40
    1230-3666
    2300-7354
    Pojawia się w:
    Fibres & Textiles in Eastern Europe
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Optimal sparse boundary control for a semilinear parabolic equation with mixed control-state constraints
    Autorzy:
    Casas, Eduardo
    Troltzsch, Fredi
    Powiązania:
    https://bibliotekanauki.pl/articles/970122.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    semilinear parabolic equation
    optimal control
    sparse boundary control
    mixed control-state constraints
    Opis:
    A problem of sparse optimal boundary control for a semilinear parabolic partial differential equation is considered, where pointwise bounds on the control and mixed pointwise control-state constraints are given. A standard quadratic objective functional is to be minimized that includes a Tikhonov regularization term and the L1-norm of the control accounting for the sparsity. Applying a recent linearization theorem, we derive first-order necessary optimality conditions in terms of a variational inequality under linearized mixed control state constraints. Based on this preliminary result, a Lagrange multiplier rule with bounded and measurable multipliers is derived and sparsity results on the optimal control are demonstrated.
    Źródło:
    Control and Cybernetics; 2019, 48, 1; 89-124
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Incoherent Discriminative Dictionary Learning for Speech Enhancement
    Autorzy:
    Shaheen, D.
    Dakkak, O. A.
    Wainakh, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/308116.pdf
    Data publikacji:
    2018
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    ADMM
    l1 minimization algorithms
    sparse coding
    speech enhancement
    supervised dictionary learning
    Opis:
    Speech enhancement is one of the many challenging tasks in signal processing, especially in the case of nonstationary speech-like noise. In this paper a new incoherent discriminative dictionary learning algorithm is proposed to model both speech and noise, where the cost function accounts for both “source confusion” and “source distortion” errors, with a regularization term that penalizes the coherence between speech and noise sub-dictionaries. At the enhancement stage, we use sparse coding on the learnt dictionary to find an estimate for both clean speech and noise amplitude spectrum. In the final phase, the Wiener filter is used to refine the clean speech estimate. Experiments on the Noizeus dataset, using two objective speech enhancement measures: frequency-weighted segmental SNR and Perceptual Evaluation of Speech Quality (PESQ) demonstrate that the proposed algorithm outperforms other speech enhancement methods tested.
    Źródło:
    Journal of Telecommunications and Information Technology; 2018, 3; 42-54
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Time-shifted Pilot-based Scheduling with Adaptive Optimization for Pilot Contamination Reduction in Massive MIMO
    Autorzy:
    Kumar, Ambala Pradeep
    Srinivasulu, Tadisetty
    Powiązania:
    https://bibliotekanauki.pl/articles/1839309.pdf
    Data publikacji:
    2020
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    massive MIMO
    pilot contamination
    sparse FCM
    time-shifted pilot scheduling
    user grouping
    Opis:
    Massive multiple-input multiple-output (MIMO) is considered to be an emerging technique in wireless communication systems, as it offers the ability to boost channel capacity and spectral efficiency. However, a massive MIMO system requires huge base station (BS) antennas to handle users and suffers from inter-cell interference that leads to pilot contamination. To cope with this, time-shifted pilots are devised for avoiding interference between cells, by rearranging the order of transmitting pilots in different cells. In this paper, an adaptive-elephant-based spider monkey optimization (adaptive ESMO) mechanism is employed for time-shifted optimal pilot scheduling in a massive MIMO system. Here, user grouping is performed with the sparse fuzzy c-means (Sparse FCM) algorithm, grouping users based on such parameters as large-scale fading factor, SINR, and user distance. Here, the user grouping approach prevents inappropriate grouping of users, thus enabling effective grouping, even under the worst conditions in which the channel operates. Finally, optimal time-shifted scheduling of the pilot is performed using the proposed adaptive ESMO concept designed by incorporating adaptive tuning parameters. The efficiency of the adaptive ESMO approach is evaluated and reveals superior performance with the highest achievable uplink rate of 43.084 bps/Hz, the highest SINR of 132.9 dB, and maximum throughput of 2.633 Mbps.
    Źródło:
    Journal of Telecommunications and Information Technology; 2020, 4; 10-21
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A proximal-based algorithm for piecewise sparse approximation with application to scattered data fitting
    Autorzy:
    Zhong, Yijun
    Li, Chongjun
    Li, Zhong
    Duan, Xiaojuan
    Powiązania:
    https://bibliotekanauki.pl/articles/2172132.pdf
    Data publikacji:
    2022
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    piecewise sparse approximation
    proximal gradient
    scattered data fitting
    aproksymacja rzadka
    gradient proksymalny
    dopasowanie danych
    Opis:
    In some applications, there are signals with a piecewise structure to be recovered. In this paper, we propose a piecewise sparse approximation model and a piecewise proximal gradient method (JPGA) which aim to approximate piecewise signals. We also make an analysis of the JPGA based on differential equations, which provides another perspective on the convergence rate of the JPGA. In addition, we show that the problem of sparse representation of the fitting surface to the given scattered data can be considered as a piecewise sparse approximation. Numerical experimental results show that the JPGA can not only effectively fit the surface, but also protect the piecewise sparsity of the representation coefficient.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2022, 32, 4; 671--682
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An autoencoder-enhanced stacking neural network model for increasing the performance of intrusion detection
    Autorzy:
    Brunner, Csaba
    Kő, Andrea
    Fodor, Szabina
    Powiązania:
    https://bibliotekanauki.pl/articles/2147134.pdf
    Data publikacji:
    2022
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    intrusion detection
    neural network
    ensemble classifiers
    hyperparameter optimization
    sparse autoencoder
    NSL-KDD
    machine learning
    Opis:
    Security threats, among other intrusions affecting the availability, confidentiality and integrity of IT resources and services, are spreading fast and can cause serious harm to organizations. Intrusion detection has a key role in capturing intrusions. In particular, the application of machine learning methods in this area can enrich the intrusion detection efficiency. Various methods, such as pattern recognition from event logs, can be applied in intrusion detection. The main goal of our research is to present a possible intrusion detection approach using recent machine learning techniques. In this paper, we suggest and evaluate the usage of stacked ensembles consisting of neural network (SNN) and autoencoder (AE) models augmented with a tree-structured Parzen estimator hyperparameter optimization approach for intrusion detection. The main contribution of our work is the application of advanced hyperparameter optimization and stacked ensembles together. We conducted several experiments to check the effectiveness of our approach. We used the NSL-KDD dataset, a common benchmark dataset in intrusion detection, to train our models. The comparative results demonstrate that our proposed models can compete with and, in some cases, outperform existing models.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 2; 149--163
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A novel method of health indicator construction and remaining useful life prediction based on deep learning
    Autorzy:
    Zhan, Xianbiao
    Liu, Zixuan
    Yan, Hao
    Wu, Zhenghao
    Guo, Chiming
    Jia, Xisheng
    Powiązania:
    https://bibliotekanauki.pl/articles/27312791.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
    Tematy:
    stacked sparse autoencoder
    health indicator
    long short-term memory network
    remaining useful life prediction
    Opis:
    The construction of health indicators (HI) for traditional deep learning requires human training labels and poor interpretability. This paper proposes an HI construction method based on Stacked Sparse Autoencoder (SSAE) and combines SSAE with Long short-term memory (LSTM) network to predict the remaining useful life (RUL). Extracting features from a single domain may result in insufficient feature extraction and cannot comprehensively reflect the degradation status information of mechanical equipment. In order to solve the problem, this article extracts features from time domain, frequency domain, and time-frequency domain to construct a comprehensive original feature set. Based on monotonicity, trendiness, and robustness, the most sensitive features from the original feature set are selected and put into the SSAE network to construct HI for state partitioning, and then LSTM is used for RUL prediction. By comparing with the existing methods, it is proved that the prediction effect of the proposed method in this paper is satisfied.
    Źródło:
    Eksploatacja i Niezawodność; 2023, 25, 4; art. no. 171374
    1507-2711
    Pojawia się w:
    Eksploatacja i Niezawodność
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Resource Tuned Optimal Random Network Coding for Single Hop Multicast future 5G Networks
    Autorzy:
    Dong, Dhawa Sang
    Pokhrel, Yagnya Murti
    Gachhadar, Anand
    Qamar, Faizan
    Amiri, Iraj Sadegh
    Maharjan, Ram Krishna
    Powiązania:
    https://bibliotekanauki.pl/articles/226605.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    coding coefficients
    computational complexity
    lower triangular matrix
    random network coding
    sparse coding
    coefficients
    Opis:
    Optimal random network coding is reduced complexity in computation of coding coefficients, computation of encoded packets and coefficients are such that minimal transmission bandwidth is enough to transmit coding coefficient to the destinations and decoding process can be carried out as soon as encoded packets are started being received at the destination and decoding process has lower computational complexity. But in traditional random network coding, decoding process is possible only after receiving all encoded packets at receiving nodes. Optimal random network coding also reduces the cost of computation. In this research work, coding coefficient matrix size is determined by the size of layers which defines the number of symbols or packets being involved in coding process. Coding coefficient matrix elements are defined such that it has minimal operations of addition and multiplication during coding and decoding process reducing computational complexity by introducing sparseness in coding coefficients and partial decoding is also possible with the given coding coefficient matrix with systematic sparseness in coding coefficients resulting lower triangular coding coefficients matrix. For the optimal utility of computational resources, depending upon the computational resources unoccupied such as memory available resources budget tuned windowing size is used to define the size of the coefficient matrix.
    Źródło:
    International Journal of Electronics and Telecommunications; 2019, 65, 3; 463-469
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A Signal Subspace Speech Enhancement Approach Based on Joint Low-Rank and Sparse Matrix Decomposition
    Autorzy:
    Sun, C.
    Xie, J.
    Leng, Y.
    Powiązania:
    https://bibliotekanauki.pl/articles/177990.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    subspace speech enhancement
    singular value decomposition
    joint low-rank and sparse matrix decomposition
    Opis:
    Subspace-based methods have been effectively used to estimate enhanced speech from noisy speech samples. In the traditional subspace approaches, a critical step is splitting of two invariant subspaces associated with signal and noise via subspace decomposition, which is often performed by singular-value decomposition or eigenvalue decomposition. However, these decomposition algorithms are highly sensitive to the presence of large corruptions, resulting in a large amount of residual noise within enhanced speech in low signal-to-noise ratio (SNR) situations. In this paper, a joint low-rank and sparse matrix decomposition (JLSMD) based subspace method is proposed for speech enhancement. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank value for the underlying clean speech matrix. Then the subspace decomposition is performed by means of JLSMD, where the decomposed low-rank part corresponds to enhanced speech and the sparse part corresponds to noise signal, respectively. An extensive set of experiments have been carried out for both of white Gaussian noise and real-world noise. Experimental results show that the proposed method performs better than conventional methods in many types of strong noise conditions, in terms of yielding less residual noise and lower speech distortion.
    Źródło:
    Archives of Acoustics; 2016, 41, 2; 245-254
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Speech emotion recognition based on sparse representation
    Autorzy:
    Yan, J.
    Wang, X.
    Gu, W.
    Ma, L.
    Powiązania:
    https://bibliotekanauki.pl/articles/177778.pdf
    Data publikacji:
    2013
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    speech emotion recognition
    sparse partial least squares regression SPLSR
    SPLSR
    feature selection and dimensionality reduction
    Opis:
    Speech emotion recognition is deemed to be a meaningful and intractable issue among a number of do- mains comprising sentiment analysis, computer science, pedagogy, and so on. In this study, we investigate speech emotion recognition based on sparse partial least squares regression (SPLSR) approach in depth. We make use of the sparse partial least squares regression method to implement the feature selection and dimensionality reduction on the whole acquired speech emotion features. By the means of exploiting the SPLSR method, the component parts of those redundant and meaningless speech emotion features are lessened to zero while those serviceable and informative speech emotion features are maintained and selected to the following classification step. A number of tests on Berlin database reveal that the recogni- tion rate of the SPLSR method can reach up to 79.23% and is superior to other compared dimensionality reduction methods.
    Źródło:
    Archives of Acoustics; 2013, 38, 4; 465-470
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    ZA-APA with Adaptive Zero Attractor Controller for Variable Sparsity Environment
    Autorzy:
    Radhika, S.
    Chandrasekar, A.
    Nirmalraj, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/1844469.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Zero Attraction APA
    sparse channel
    convergence
    steady state mean square error
    variable zero attraction controller
    Opis:
    The zero attraction affine projection algorithm (ZA-APA) achieves better performance in terms of convergence rate and steady state error than standard APA when the system is sparse. It uses l1 norm penalty to exploit sparsity of the channel. The performance of ZA-APA depends on the value of zero attractor controller. Moreover a fixed attractor controller is not suitable for varying sparsity environment. This paper proposes an optimal adaptive zero attractor controller based on Mean Square Deviation (MSD) error to work in variable sparsity environment. Experiments were conducted to prove the suitability of the proposed algorithm for identification of unknown variable sparse system.
    Źródło:
    International Journal of Electronics and Telecommunications; 2020, 66, 4; 695-700
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Large-scale hyperspectral image compression via sparse representations based on online learning
    Autorzy:
    Ülkü, İ.
    Kizgut, E.
    Powiązania:
    https://bibliotekanauki.pl/articles/331241.pdf
    Data publikacji:
    2018
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    hyperspectral imaging
    compression algorithm
    dictionary learning
    sparse coding
    obrazowanie wielospektralne
    algorytm kompresji
    nauczanie online
    kodowanie rzadkie
    Opis:
    In this study, proximity based optimization algorithms are used for lossy compression of hyperspectral images that are inherently large scale. This is the first time that such proximity based optimization algorithms are implemented with an online dictionary learning method. Compression performances are compared with the one obtained by various sparse representation algorithms. As a result, proximity based optimization algorithms are listed among the three best ones in terms of compression performance values for all hyperspectral images. Additionally, the applicability of anomaly detection is tested on the reconstructed images.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2018, 28, 1; 197-207
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A parallel block Lanczos algorithm and its implementation for the evaluation of some eigenvalues of large sparse symmetric matrices on multicomputers
    Autorzy:
    Guarracino, M. R.
    Perla, F.
    Zanetti, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/908413.pdf
    Data publikacji:
    2006
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    cluster architecture
    symmetric block Lanczos algorithm
    sparse matrices
    parallel eigensolver
    algorytm Lanczosa
    macierze rzadkie
    architektura klastrowa
    Opis:
    In the present work we describe HPEC (High Performance Eigenvalues Computation), a parallel software package for the evaluation of some eigenvalues of a large sparse symmetric matrix. It implements an efficient and portable Block Lanczos algorithm for distributed memory multicomputers. HPEC is based on basic linear algebra operations for sparse and dense matrices, some of which have been derived by ScaLAPACK library modules. Numerical experiments have been carried out to evaluate HPEC performance on a cluster of workstations with test matrices from Matrix Market and Higham’s collections. A comparison with a PARPACKroutine is also detailed. Finally, parallel performance is evaluated on random matrices, using standard parameters.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2006, 16, 2; 241-249
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Phonetic Segmentation using a Wavelet-based Speech Cepstral Features and Sparse Representation Classifier
    Autorzy:
    Al-Hassani, Ihsan
    Al-Dakkak, Oumayma
    Assami, Abdlnaser
    Powiązania:
    https://bibliotekanauki.pl/articles/2058484.pdf
    Data publikacji:
    2021
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    Arabic speech corpus
    ASR
    F1-score
    phonetic segmentation
    sparse representation classifier
    TTS
    wavelet packet
    Opis:
    Speech segmentation is the process of dividing speech signal into distinct acoustic blocks that could be words, syllables or phonemes. Phonetic segmentation is about finding the exact boundaries for the different phonemes that composes a specific speech signal. This problem is crucial for many applications, i.e. automatic speech recognition (ASR). In this paper we propose a new model-based text independent phonetic segmentation method based on wavelet packet speech parametrization features and using the sparse representation classifier (SRC). Experiments were performed on two datasets, the first is an English one derived from TIMIT corpus, while the second is an Arabic one derived from the Arabic speech corpus. Results showed that the proposed wavelet packet decomposition features outperform the MFCC features in speech segmentation task, in terms of both F1-score and R-measure on both datasets. Results also indicate that the SRC gives higher hit rate than the famous k-Nearest Neighbors (k-NN) classifier on TIMIT dataset.
    Źródło:
    Journal of Telecommunications and Information Technology; 2021, 4; 12--22
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Composition of wavelet and Fourier transforms
    Autorzy:
    Ziółko, Mariusz
    Witkowski, Marcin
    Gałka, Jakub
    Powiązania:
    https://bibliotekanauki.pl/articles/747314.pdf
    Data publikacji:
    2018
    Wydawca:
    Polskie Towarzystwo Matematyczne
    Tematy:
    wavelet transform, Fourier transform, numerical methods, sparse systems
    Transformacja falkowa, transformacja Fouriera, metody numeryczne, systemy rzadkie
    Opis:
    W pracy przedstawione są podstawowe własności szeregowego złożenia dwóch transformacji: falkowej i Fouriera. Uzyskano dwa rodzaje transformacji ponieważ transformacje falkowe i Fouriera nie są przemienne. Przedstawione są konsekwencje zjawiska zwanego "przestępstwem falkowym". Zastosowanie falek ze zwartymi nośnikami w dziedzinie częstotliwości (np. falki Meyera) prowadzi do reprezentacji sygnałów w postaci macierzy rzadkich. Sygnały mowy zostały użyte do przetestowania przedstawionych transformacji.
    The paper presents the basic properties of the serial composition of two transformations: wavelet and Fourier. Two types of transformations were obtained because wavelet and Fourier transformations do not commute. The consequences of a phenomenon known as a "wavelet crime" are presented. Using wavelets with compact support in the frequency domain (e.g. Meyer wavelets) leads to the representation of signals as sparse matrices. Speech signals were used to test the presented transforms.
    Źródło:
    Mathematica Applicanda; 2018, 46, 1
    1730-2668
    2299-4009
    Pojawia się w:
    Mathematica Applicanda
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Overview of adaptive and low-rank approximation algorithms for modeling influence of electromagnetic waves generated by cellphone antenna on human head
    Autorzy:
    Głut, Barbara
    Paszyński, Maciej
    Powiązania:
    https://bibliotekanauki.pl/articles/2097964.pdf
    Data publikacji:
    2021
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    mesh generation
    mesh adaptation
    Pennes bioheat equations
    time-harmonic Maxwell equations
    sparse factorization
    low rank approximation
    Opis:
    This paper presents an overview of formulations and algorithms that are dedicated to modeling the influence of electromagnetic waves on the human head. We start from h adaptive approximation of a three-dimensional MRI scan of the human head. Next, we solve the time-harmonic Maxwell equations with a 1.8 GHz cellphone antenna. We compute the specific absorption rate used as the heat source for the Pennes bioheat equation modeling the heat generated by EM waves inside the head. We propose an adaptive algorithm mixed with time-stepping iterations where we simultaneously refine the computational mesh, solve the Maxwell and Pennes equations, and iterate the time steps. We employ the sparse Gaussian elimination algorithm with the low-rank compres-sion of the off-diagonal matrix blocks for the factorization of the matrices. We conclude with the statement that 15 minutes of talking with a 1.8 GHz antenna with one watt of power results in increased brain tissue temperatures (up to 38.4◦C).
    Źródło:
    Computer Science; 2021, 22 (4); 433--461
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Quick offline sparse matrices
    Szybkie rzadkie macierze przechowywane na dysku
    Autorzy:
    Wicijowski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/160240.pdf
    Data publikacji:
    2010
    Wydawca:
    Sieć Badawcza Łukasiewicz - Instytut Elektrotechniki
    Tematy:
    macierz rzadka
    mnożenie
    przechowywanie w trybie offline
    wielki zbiór danych
    sparse matrix
    multiplication
    offline storage
    huge datasets
    Opis:
    When dealing with large datasets, computer memory constraints are a common problem. With the volumes of data exceeding 1 GiB of size, storage of the whole datasets in RAM becomes infeasible. Since in most applications one deals with only a portion of dataset at a time, the rest may be kept offline on nonvolatile memory that provides larger capacities. The access to nonvolatile memory is typically a few orders of magnitude slower than of RAM, so an efficient method of storage should be proposed to keep the number of disc accesses count as small as possible. In the paper I describe the offline storage of sparse matrices that is built on top of Hierarchical Data Format (precisely, on the latest revision - HDF5) addressing the problem of matrix-vector multiplication.
    Ograniczenia pamięci komputera są powszechnym problemem przy obliczeniach przeprowadzanych na wielkich zbiorach danych. Przy danych roboczych przekraczających 1 GiB, składowanie całości w pamięci operacyjnej staje się utrudnione, a często nawet nieosiągalne. Ponieważ w większości aplikacji wykonuje się działania jedynie na fragmencie zbioru danych, reszta może być przechowywana w pamięci stałej, która zapewnia dużo większe pojemności. Dostęp do pamięci stałej jest zazwyczaj kilka rzędów wielkości wolniejszy niż do RAMu, zatem należy przedstawić metodę składowania ograniczającą do minimum ilość dostępów do dysku. W artykule opisuję format przechowywania macierzy rzadkich na dysku, zbudowanym na bazie formatu HDF5 (Hierarchical Data Format) pod kątem minimalizacji czasu mnożenia tej macierzy przez wektor.
    Źródło:
    Prace Instytutu Elektrotechniki; 2010, 247; 209-222
    0032-6216
    Pojawia się w:
    Prace Instytutu Elektrotechniki
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Localizing influential genes with modified versions of Bayesian Information Criterion
    Autorzy:
    Bogdan, Małgorzata
    Szulc, Piotr
    Powiązania:
    https://bibliotekanauki.pl/articles/748746.pdf
    Data publikacji:
    2012
    Wydawca:
    Polskie Towarzystwo Matematyczne
    Tematy:
    genetyka statystyczna, wybór modelu, rzadka regresja liniowa,
    statistical genetics, quantitative trait loci, model selection, sparse linear regression, Bayesian Information Criterion
    Opis:
    W ostatnich latach nastąpił bardzo szybki rozwój technologii  wspomagających badania w genetyce. Rezultatem tego postępu są olbrzymie zbiory danych. Skuteczne pozyskiwanie informacji z takich zbiorów wymaga scisłej współpracy między genetykami, informatykami oraz statystykami. Rolą statystyków jest okreslenie precyzyjnych kryteriów gwarantujących efektywne oddzielenie istotnej informacji od losowych zakłócen. W szczególnosci, duze rozmiary tych zbiorów wymagają opracowania nowych metod korekty na wielokrotne testowanie oraz nowych kryteriów wyboru istotnych zmiennych objasniających. Szczególnym przykładem identyfikacji zmiennych objasniających jest problem lokalizacji genów odpowiedzialnych za cechy ilosciowe (Quantitative Trait Loci, QTL).Do lokalizacji genów stosuje się tzw. markery molekularne. Są to fragmenty łancucha DNA, które mogą występowac w róznych wariantach (allelach) u róznych jednostek w populacji. Postac danego markera u badanego osobnika mozna ustalic eksperymentalnie.U organizmów diploidalnych, u których chromosomy występują w parach, genotyp danego markera jest wyspecyfikowany przez podanie alleli występujących na obu chromosomach. Z punktu widzenia statystyka genotypy markerów stanowią jakosciowe zmienne objasniające. Jezeli dany marker znajduje się blisko genu wpływającego na badaną cechę, to mozemy spodziewac się  statystycznej zaleznosci między genotypem w tym markerze a badaną cechą ilosciową.Do identyfikacji istotnych markerów genetycznych zwykle stosuje się model regresji wielorakiej. Liczbę zmiennych niezaleznych mozna w tej sytuacji szacowac za pomocą jednego z  wielu kryteriów wyboru modelu. Niestety, okazuje się, ze w kontekscie genetycznym, gdzie liczba markerów istotnie przewyzsza liczbę obserwacji, klasyczne kryteria wyboru modelu przeszacowują liczbę istotnych zmiennych.Aby rozwiązac ten problem ostatnio wprowadzono kilka nowych modyfikacji Bayesowskiego Kryterium Informacyjnego. W tym artykule zaprezentujemy trzy z tych modyfikacji, podamy wyniki dotyczące zgodnosci tych metod w sytuacji gdy liczba dostępnych markerów genetycznych rosnie wraz z rozmiarem próby oraz wyniki symulacji komputerowych ilustrujących działanie tych metod w kontekscie genetycznym.
    Regions of the genome that influence quantitative traits are called quantitative trait loci (QTLs) and can be located using statistical methods. For this aim scientists use genetic markers, whose genotypes are known, and look for the associations between these genotypes and trait values. The common method which can be used in this problem is a linear regression. There are many model selection criteria for the choice of predictors in a linear regression. However, in the context of QTL mapping, where the number of available markers $p_n$ is usually  bigger than the sample size $n$, the classical criteria overestimate the number of regressors. To solve this problem several modifications of the {\it Bayesian Information Criterion} have been proposed and it has been recently proved that at least three of them, EBIC, mBIC and mBIC2, are consistent (also in case when $p_n>n$). In this article we discuss these criteria and their asymptotic properties and compare them by an extensive simulation study in the genetic context.
    Źródło:
    Mathematica Applicanda; 2012, 40, 1
    1730-2668
    2299-4009
    Pojawia się w:
    Mathematica Applicanda
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Electronic structures of CdSe quantum dots embedded in ZnSe
    Autorzy:
    Jayawardhana, M. R. P. I.
    Wijewardena Gamalath, K. A. I. L.
    Powiązania:
    https://bibliotekanauki.pl/articles/1178287.pdf
    Data publikacji:
    2017
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    LCAO method
    Quantum dot
    Sparse matrices
    adjacency matrix
    folded spectrum method
    optical matrix elements
    strain effects
    valence band offset
    Opis:
    The electronic structures and optical matrix elements of CdSe semiconductor quantum dots of near cubical, hemispherical and cylindrical shape embedded in ZnSe were calculated. Bulk Hamiltonian matrices were obtained using the empirical tight binding method including spin-orbital coupling and relativistic effects. All quantum dots were simulated in reciprocal space and the number of atoms in each quantum dot was kept nearly equal for the comparison purpose. An adjacency matrix was produced which indicates the adjacencies of unit cells and the bulk Hamiltonian was included for each adjacency point in order to obtain the quantum dot Hamiltonians. The strain effects, valence band offset and spin orbital coupling were included in the calculations. The quantum dot Hamiltonian was solved to obtain the highest and lowest eigenvalues from which the electronic structure was obtained. Then eigenvalues near integers ranging from the lowest eigenvalue to highest eigenvalue was generated for the point.
    Źródło:
    World Scientific News; 2017, 86, 3; 205-225
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Forecasting study of mains reliability based on sparse field data and perspective state space models
    Prognozowanie niezawodności elementów sieci wodociągowej na podstawie rzadkich danych terenowych i modeli przestrzeni stanów
    Autorzy:
    Valis, David
    Forbelská, Marie
    Vintr, Zdeněk
    Powiązania:
    https://bibliotekanauki.pl/articles/301060.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
    Tematy:
    mains
    critical infrastructure
    reliability prognosis
    sparse data
    state space models
    sieć wodociągowa
    infrastruktura krytyczna
    prognoza niezawodności
    rzadkie dane
    model przestrzeni stanów
    Opis:
    The elements of critical infrastructure have to meet demanding dependability, safety and security requirements. The article deals with the prognosis of water mains reliability while using sparse irregular filed data. The data are sparse because the only thing we know is the number of mains failures during a given month. Since it is possible to transform the data into a typical reliability measure (rate of failure occurrence – ROCOF), we can examine the course of this measure development in time. In order to model and predict the ROCOF development, we suggest novel single and multiple error state space models. The results can be used for i) optimizing mains operation and maintenance, ii) estimating life cycle cost, and iii) planning crisis management.
    Elementy infrastruktury krytycznej muszą spełniać wysokie wymagania w zakresie niezawodności, bezpieczeństwa i ochrony. Artykuł dotyczy prognozowania niezawodności sieci wodociągowej przy wykorzystaniu nieregularnie rejestrowanych rzadkich danych. Wykorzystane w pracy dane są rzadkie, ponieważ dostarczają jedynie informacji na temat liczby uszkodzeń wodociągu w danym miesiącu. Przekształcenie tych danych w typową miarę niezawodności (wskaźnik występowania uszkodzeń – ROCOF), pozwala zbadać przebieg rozwoju tej miary w czasie. Rozwój ROCOF można modelować i przewidywać za pomocą zaproponowanych w pracy innowacyjnych modeli przestrzeni stanów uwzględniających pojedynczy błąd lub wiele błędów. Uzyskane wyniki można wykorzystać do i) optymalizacji pracy i eksploatacji sieci wodociągowej, ii) szacowania kosztów cyklu życia, oraz iii) planowania zarządzania kryzysowego.
    Źródło:
    Eksploatacja i Niezawodność; 2020, 22, 2; 179-191
    1507-2711
    Pojawia się w:
    Eksploatacja i Niezawodność
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Efficient simulations of large-scale convective heat transfer problems
    Autorzy:
    Goik, Damian
    Banaś, Krzysztof
    Bielański, Jan
    Chłoń, Kazimierz
    Powiązania:
    https://bibliotekanauki.pl/articles/2097965.pdf
    Data publikacji:
    2021
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    convective heat transfer
    finite element method
    sparse linear equations
    algebraic multigrid
    Navier–Stokes equations
    GMRES
    block preconditioning
    SUPG stabilization
    MPI
    PETSc
    scalability
    Opis:
    We describe an approach for efficient solution of large-scale convective heat transfer problems that are formulated as coupled unsteady heat conduction and incompressible fluid-flow equations. The original problem is discretized over time using classical implicit methods, while stabilized finite elements are used for space discretization. The algorithm employed for the discretization of the fluid-flow problem uses Picard’s iterations to solve the arising nonlinear equations. Both problems (the heat transfer and Navier–Stokes equations) give rise to large sparse systems of linear equations. The systems are solved by using an iterative GMRES solver with suitable preconditioning. For the incompressible flow equations, we employ a special preconditioner that is based on an algebraic multigrid (AMG) technique. This paper presents algorithmic and implementation details of the solution procedure, which is suitably tuned – especially for ill-conditioned systems that arise from discretizations of incompressible Navier–Stokes equations. We describe a parallel implementation of the solver using MPI and elements from the PETSC library. The scalability of the solver is favorably compared with other methods, such as direct solvers and the standard GMRES method with ILU preconditioning.
    Źródło:
    Computer Science; 2021, 22 (4); 517--538
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Reduction of BER using RSC code for Optical Code Division Multiple Access Networks
    Autorzy:
    Panda, Satyasen
    Powiązania:
    https://bibliotekanauki.pl/articles/1178316.pdf
    Data publikacji:
    2017
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    Cross Correlation (CC)
    Multiple Access Interface (MAI)
    Optical Code Division Multiple Access (OCDMA)
    Random Sparse Code (RSC)
    Wavelength hopping time spreading (WHTS)
    Opis:
    In this study, a two dimensional (2-D) wavelength hopping and time spreading (WHTS) optical code division multiple access (OCDMA) code is designed using Sparse ruler technique. The proposed 64 bit 2-D code is constructed by an algorithm based on random spacing of sparse codes referred in this work as Random Sparse Code (RSC). The performance of the proposed 2-D RSC is evaluated in terms of bit error rate (BER), received signal power and time domain analysis of received signals. The system performance of the OCDMA system utilizing 2-D RSC code improved significantly due to less BER, low cross correlation property and simple encoder/decoder design. The output BER is much lower at a data rate of 1.25 gbps and 2.5 gbps for a distance of 100 km with ITU-T standard single mode fiber with attenuation level of 0.2dB/km.
    Źródło:
    World Scientific News; 2017, 81, 2; 106-120
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Diagnostyka silnika synchronicznego oparta na rozpoznawaniu dźwięku z zastosowaniem LPCC i GSDM
    Diagnostics of a synchronous motor based on sound recognition with application of LPCC and GSDM
    Autorzy:
    Głowacz, A.
    Głowacz, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/156930.pdf
    Data publikacji:
    2010
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    silnik synchroniczny
    rozpoznawanie dźwięku
    LPCC
    GSDM
    diagnostyka
    synchronous motor
    sound recognition
    LPCC (Linear Predictive Cepstrum Coefficients)
    GSDM (Genetic Sparse Distributed Memory)
    diagnostics
    Opis:
    Zaprezentowano koncepcję badania sygnałów akustycznych stanów przedawaryjnych silnika synchronicznego. Oprogramowanie do rozpoznawania dźwięku zostało zaimplementowane. Algorytmy przetwarzania i analizy sygnałów akustycznych zostały zastosowane. System jest oparty na algorytmie LPCC (Współczynniki cepstralne liniowego kodowania) i GSDM (Genetyczna rozrzedzona pamięć rozproszona). Badania zostały przeprowadzone dla sygnałów akustycznych stanów przedawaryjnych. Zmiany w sygnale akustycznym spowodowane były przez zwarcia i przerwy w obwodzie stojana. Analiza wyników pokazuje wrażliwość metody opartej na LPCC i GSDM w zależności od danych wejściowych. Wyniki badań potwierdzają poprawne działanie systemu rozpoznawania dźwięku silnika synchronicznego.
    In recent years the methods of sound recognition have been de-veloped. Hence, there is an idea to use them in case of machines. The paper describes the concept of investigations of acoustic signals of synchronous motor imminent failure conditions. Measurements were taken with a recorder OLYMPUS WS-200S. Sound recognition software was implemented. Algorithms of signal processing and analysis were used. The system is based on the LPCC (Linear Predictive Cepstrum Coefficients) algorithm and GSDM (Genetic Sparse Distributed Memory). Investigations were carried out for acoustic signals of imminent failure conditions. The following plan of investigations of a synchronous motor acoustic signal was proposed: recording of audio track, sound track division, sampling, quantization, normalization, filtration, windowing, feature extraction, classification (Fig. 2). Figs. 3, 4, 5 and 6 show changes of the LPCC values for four types of the categories recognized. Changes in the acoustic signal were caused by short circuit and broken coils in the stator circuit. The sound recognition efficiency depending on the acoustic signal and the sample length is presented in Fig. 8. The sound recognition system was built for a synchronous motor. There were used 39 band-pass filters in investigations. Analysis of the results shows the sensitivity of the method based on LPCC and GSDM, depending on the input data. The results confirm correct operation of the synchronous motor sound recognition system. These studies can be used for diagnostics based on acoustic emission in electrical, mechanical, hydraulic and pneumatic machines.
    Źródło:
    Pomiary Automatyka Kontrola; 2010, R. 56, nr 5, 5; 479-482
    0032-4140
    Pojawia się w:
    Pomiary Automatyka Kontrola
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Diagnostyka silnika synchronicznego oparta na rozpoznawaniu dźwięku z zastosowaniem FFT i GSDM
    Synchronous motor diagnostics based on sound recognition with use of FFT and GSDM
    Autorzy:
    Głowacz, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/187768.pdf
    Data publikacji:
    2010
    Wydawca:
    Sieć Badawcza Łukasiewicz - Instytut Technik Innowacyjnych EMAG
    Tematy:
    diagnostyka
    szybka transformacja Fouriera
    GSDM (genetyczna rozrzedzona pamięć rozproszona)
    silnik synchroniczny
    diagnostics
    fast Fourier transform (FFT)
    GSDM (Genetic Sparse Distributed Memory)
    synchronous motor
    Opis:
    Zamierzeniem pracy jest przedstawienie metody rozpoznawania dźwięku silnika synchronicznego wykorzystującej FFT i GSDM. Badania rozpoznawania dźwięków przeprowadzono dla silnika synchronicznego podczas pracy bez uszkodzeń, ze zwarciem zezwojów w obwodzie stojana, z jedną przerwą w obwodzie stojana i z trzema przerwami w obwodzie stojana. Wyniki badań potwierdzają dużą skuteczność rozpoznawania dźwięku w silniku synchronicznym.
    The work has aimed to present a method of sound recognition of a synchronous motor with use of FFT and GSDM. The research on sound recognition has been done for a synchronous motor during operation without any failures, then in case of a short-circuit of coils in stator circuit, in case of one break in stator circuit and three breaks in stator circuit. The research results have validated a high effectiveness of sound recognition in a synchronous motor.
    Źródło:
    Mechanizacja i Automatyzacja Górnictwa; 2010, R. 48, nr 3, 3; 25-29
    0208-7448
    Pojawia się w:
    Mechanizacja i Automatyzacja Górnictwa
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Modified Block Sparse Bayesian Learning-Based Compressive Sensing Scheme For EEG Signals
    Autorzy:
    Upadhyaya, Vivek
    Salim, Mohammad
    Powiązania:
    https://bibliotekanauki.pl/articles/1844532.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    compressive sensing
    CS
    mean square error
    MSE
    structural similarity index measure
    SSIM
    electroencephalogram
    EEG
    digital signal processing
    DSP
    block sparse Bayesian learning
    BSBL
    Opis:
    Advancement in medical technology creates some issues related to data transmission as well as storage. In real-time processing, it is too tedious to limit the flow of data as it may reduce the meaningful information too. So, an efficient technique is required to compress the data. This problem arises in Magnetic Resonance Imaging (MRI), Electrocardiogram (ECG), Electroencephalogram (EEG), and other medical signal processing domains. In this paper, we demonstrate Block Sparse Bayesian Learning (BSBL) based compressive sensing technique on an Electroencephalogram (EEG) signal. The efficiency of the algorithm is described using the Mean Square Error (MSE) and Structural Similarity Index Measure (SSIM) value. Apart from this analysis we also use different combinations of sensing matrices too, to demonstrate the effect of sensing matrices on MSE and SSIM value. And here we got that the exponential and chi-square random matrices as a sensing matrix are showing a significant change in the value of MSE and SSIM. So, in real-time body sensor networks, this scheme will contribute a significant reduction in power requirement due to its data compression ability as well as it will reduce the cost and the size of the device used for real-time monitoring.
    Źródło:
    International Journal of Electronics and Telecommunications; 2021, 67, 3; 331-336
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Analiza pracy przekształtnika SMC sterowanego metodą wektora przestrzennego
    Analysis of the sparse matrix converter controlled by space vector modulation
    Autorzy:
    Suliga, Mateusz
    Powiązania:
    https://bibliotekanauki.pl/articles/37515964.pdf
    Data publikacji:
    2022
    Wydawca:
    Politechnika Rzeszowska im. Ignacego Łukasiewicza. Oficyna Wydawnicza
    Tematy:
    pośredni przekształtnik matrycowy
    IMC
    SMC
    wektorowa modulacja szerokości impulsu
    SVM
    przemiennik częstotliwości
    Indirect Matrix Converter
    Sparse Matrix Converter
    Space Vector Modulation
    frequency converter
    SV
    Opis:
    Artykuł prezentuje badania symulacyjne pośredniego przekształtnika matrycowego o topologii Sparse Matrix Converter (SMC). W porównaniu do standardowego układu przekształtnika matrycowego, topologia SMC wykorzystuje mniej elementów półprzewodnikowych, co zmniejsza cenę wykonania układu. Do sterowania łącznikami została wybrana metoda sterowania wektorowego, Space Vector Modulation (SVM). Wynikiem przeprowadzonych badań są przebiegi kształtowanych napięć wyjściowego oraz prądów wejściowych przekształtnika. Wyznaczone spektrum harmonicznych przebiegów potwierdza poprawność działania zaprojektowanego modelu przekształtnika oraz przedstawia procentową zawartość wyższych harmonicznych. Układ typu SMC spełnia założenia związane z przekształtnikami matrycowymi, przy jednoczesnym wykorzystaniu mniejszej ilości elementów półprzewodnikowych.
    This article presents simulation studies of Sparse Matrix Converter (SMC). Compared to the standard Indirect Matrix Converter (IMC), the SMC topology uses fewer semiconductor elements, witch reduces cost of the converter. The Space Vector Modulation (SVM) is used to control each of the switches. The results of the conducted tests are waveform of output voltages and input currents of the converters. The determined spectrum of harmonic waveforms confirms the correct operation of the designed converter model and presents the percentage content of higher harmonics. The SMC topology meet the assumptions related to matrix converters, while using fewer number of semiconductor elements.
    Źródło:
    Zeszyty Naukowe Politechniki Rzeszowskiej. Elektrotechnika; 2022, 39; 83-92
    0209-2662
    2300-6358
    Pojawia się w:
    Zeszyty Naukowe Politechniki Rzeszowskiej. Elektrotechnika
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Localization of genes
    Autorzy:
    Szulc, Piotr
    Powiązania:
    https://bibliotekanauki.pl/articles/748362.pdf
    Data publikacji:
    2015
    Wydawca:
    Polskie Towarzystwo Matematyczne
    Tematy:
    genetyka statystyczna, wybór modelu, rzadka regresja liniowa, bayesowskie kryterium informacyjne, ilościowa analiza lokalizacji genów
    statistical genetics, quantitative trait loci, model selection, sparse linear regression, Bayesian Information Criterion
    Opis:
    Rozwój genetyki w ostatnich latach doprowadził do sytuacji, w której jesteśmy w stanie przyjrzeć się łańcuchom DNA z dużą precyzją i zebrać ogromne ilości informacji. Oprócz tego okazało się, że zależności między genami a cechami są bardziej skomplikowane niż się wcześniej wydawało. Te dwie rzeczy spowodowały, że niezbędna stała się ścisła współpraca między genetykami a matematykami, których zadaniem jest opracowanie specjalnych metod, radzących sobie w specyficznych i trudnych problemach genetycznych. Artykuł zawiera przegląd zarówno klasycznych jak i najnowszych podejść do problemu lokalizacji genów, czyli wskazywania miejsc w łańcuchu DNA, które istotnie wpływają na interesujące nas cechy. Z powodu nie najlepszej komunikacji między matematykami i genetykami, znajomość metody innych niż klasyczne wśród tej drugiej grupy jest wciąż niewielka.
    Development of genetics in recent years has led to a situation in which we are able to look at the DNA chains with high precision and collect vast amounts of information. In addition, it turned out that the relationships between genes and traits are more complex than previously thought. These two things caused the need for close collaboration between geneticists and mathematicians whose task is to develop special methods, coping with specific and difficult genetic problems. The article includes an overview of both classic and the latest approaches to the problem of localizing genes that indicate places in the DNA chain, which significantly influence the traits of interest to us. Because of not the best communication between mathematicians and geneticists, knowledge of methods other than the classic among the latter group is still small.
    Źródło:
    Mathematica Applicanda; 2015, 43, 1
    1730-2668
    2299-4009
    Pojawia się w:
    Mathematica Applicanda
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Two implementations of the preconditioned conjugate gradient method on heterogeneous computing grids
    Autorzy:
    Collignon, T. P.
    Van Gijzen, M. B.
    Powiązania:
    https://bibliotekanauki.pl/articles/907778.pdf
    Data publikacji:
    2010
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    przetwarzanie siatkowe
    system liniowy
    metoda iteracyjna
    gradient sprzężony
    przepływ pęcherzykowy
    grid computing
    large sparse linear systems
    iterative methods
    conjugate gradient method
    Chronopoulos/Gear CG
    GridSolve middleware
    bubbly flows
    Opis:
    Efficient iterative solution of large linear systems on grid computers is a complex problem. The induced heterogeneity and volatile nature of the aggregated computational resources present numerous algorithmic challenges. This paper describes a case study regarding iterative solution of large sparse linear systems on grid computers within the software constraints of the grid middleware GridSolve and within the algorithmic constraints of preconditioned Conjugate Gradient (CG) type methods. We identify the various bottlenecks induced by the middleware and the iterative algorithm. We consider the standard CG algorithm of Hestenes and Stiefel, and as an alternative the Chronopoulos/Gear variant, a formulation that is potentially better suited for grid computing since it requires only one synchronisation point per iteration, instead of two for standard CG. In addition, we improve the computation-to-communication ratio by maximising the work in the preconditioner. In addition to these algorithmic improvements, we also try to minimise the communication overhead within the communication model currently used by the GridSolve middleware. We present numerical experiments on 3D bubbly flow problems using heterogeneous computing hardware that show lower computing times and better speed-up for the Chronopoulos/Gear variant of conjugate gradients. Finally, we suggest extensions to both the iterative algorithm and the middleware for improving granularity.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2010, 20, 1; 109-121
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Polynomial chaos expansion method in estimating probability distribution of rotor-shaft dynamic responses
    Autorzy:
    Lasota, R.
    Stocki, R.
    Tauzowski, P.
    Szolc, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/200053.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    stochastic moment estimation
    sparse polynomial chaos expansion
    maximum entropy principle
    rotor
    uncertainties
    hybrid mechanical model
    random unbalance distribution
    zasada maksymalnej entropii
    wirnik
    niepewności
    model hybrydowy
    losowy rozkład asymetrii
    Opis:
    The main purpose of the study is an assessment of computational efficiency of selected numerical methods for estimation of vibrational response statistics of a large multi-bearing turbo-generator rotor-shaft system. The effective estimation of the probability distribution of structural responses is essential for robust design optimization and reliability analysis of such systems. The analyzed scatter of responses is caused by random residual unbalances as well as random stiffness and damping parameters of the journal bearings. A proper representation of these uncertain parameters leads to multidimensional stochastic models. Three estimation techniques are compared: Monte Carlo sampling, Latin hypercube sampling and the sparse polynomial chaos expansion method. Based on the estimated values of the first four statistical moments the probability density function of the maximal vibration amplitude is evaluated by the maximal entropy principle method. The method is inherently suited for an accurate representation of the probability density functions with an exponential behavior, which appears to be characteristic for the investigated rotor-shaft responses. Performing multiple numerical tests for a range of sample sizes it was found that the sparse polynomial chaos method provides the best balance between the accuracy and computational effectiveness in estimating the unknown probability distribution of the maximal vibration amplitude.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2015, 63, 2; 413-422
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-57 z 57

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