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Wyświetlanie 1-10 z 76
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:
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:
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:
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:
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:
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:
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:
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
Wyświetlanie 1-10 z 76

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