Temat: SPARSE - Katalog OPAC zbiorów

Skocz do pozycji: 1.

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

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Skocz do pozycji: 2.

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

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Skocz do pozycji: 3.

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

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Skocz do pozycji: 4.

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

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Skocz do pozycji: 5.

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

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Skocz do pozycji: 6.

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

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Skocz do pozycji: 7.

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

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Skocz do pozycji: 8.

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

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Skocz do pozycji: 9.

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

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Skocz do pozycji: 10.

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

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