Improved Singular Value Decomposition (TopSVD) for Source Number Estimation of Low SNR in Blind Source Separation

Improved Singular Value Decomposition (TopSVD) for Source Number Estimation of Low SNR in Blind Source Separation

An improved singular value decomposition based on Toeplitz (TopSVD) is proposed to solve the problem of inaccurately estimating source numbers under the condition of a low signal-to-noise (SNR) ratio for blind source separation. First, Toeplitz modifies the covariance of the received data, and singu...

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Main Authors: Hongchun Sun, Jingzheng Guo, Liang Fang
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Blind source separation
singular value decomposition
toeplitz
low SNR
Online Access:https://ieeexplore.ieee.org/document/8047238/
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spelling doaj-ab845ccb9e7844638b5dae1952398c592021-03-29T20:19:25ZengIEEEIEEE Access2169-35362017-01-015264602646510.1109/ACCESS.2017.27544878047238Improved Singular Value Decomposition (TopSVD) for Source Number Estimation of Low SNR in Blind Source SeparationHongchun Sun0https://orcid.org/0000-0003-0122-1019Jingzheng Guo1Liang Fang2School of Mechanical Engineering and Automation, Northeastern University, Shenyang, ChinaSchool of Mechanical Engineering and Automation, Northeastern University, Shenyang, ChinaSchool of Mechanical Engineering and Automation, Northeastern University, Shenyang, ChinaAn improved singular value decomposition based on Toeplitz (TopSVD) is proposed to solve the problem of inaccurately estimating source numbers under the condition of a low signal-to-noise (SNR) ratio for blind source separation. First, Toeplitz modifies the covariance of the received data, and singular value decomposition is used to estimate the number of signal sources. The advantages of TopSVD over traditional approaches are demonstrated by simulated signals. The results demonstrate that the proposed method can be used to estimate the number of coherent sources under low SNR conditions; at the same time, it can significantly improve the accuracy of source number estimation under the conditions of a low SNR and coherent signal source with the simple algorithm.https://ieeexplore.ieee.org/document/8047238/Blind source separationsingular value decompositiontoeplitzlow SNR
collection DOAJ
language English
format Article
sources DOAJ
author Hongchun Sun
Jingzheng Guo
Liang Fang
spellingShingle Hongchun Sun
Jingzheng Guo
Liang Fang
Improved Singular Value Decomposition (TopSVD) for Source Number Estimation of Low SNR in Blind Source Separation
IEEE Access
Blind source separation
singular value decomposition
toeplitz
low SNR
author_facet Hongchun Sun
Jingzheng Guo
Liang Fang
author_sort Hongchun Sun
title Improved Singular Value Decomposition (TopSVD) for Source Number Estimation of Low SNR in Blind Source Separation
title_short Improved Singular Value Decomposition (TopSVD) for Source Number Estimation of Low SNR in Blind Source Separation
title_full Improved Singular Value Decomposition (TopSVD) for Source Number Estimation of Low SNR in Blind Source Separation
title_fullStr Improved Singular Value Decomposition (TopSVD) for Source Number Estimation of Low SNR in Blind Source Separation
title_full_unstemmed Improved Singular Value Decomposition (TopSVD) for Source Number Estimation of Low SNR in Blind Source Separation
title_sort improved singular value decomposition (topsvd) for source number estimation of low snr in blind source separation
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2017-01-01
description An improved singular value decomposition based on Toeplitz (TopSVD) is proposed to solve the problem of inaccurately estimating source numbers under the condition of a low signal-to-noise (SNR) ratio for blind source separation. First, Toeplitz modifies the covariance of the received data, and singular value decomposition is used to estimate the number of signal sources. The advantages of TopSVD over traditional approaches are demonstrated by simulated signals. The results demonstrate that the proposed method can be used to estimate the number of coherent sources under low SNR conditions; at the same time, it can significantly improve the accuracy of source number estimation under the conditions of a low SNR and coherent signal source with the simple algorithm.
topic Blind source separation
singular value decomposition
toeplitz
low SNR
url https://ieeexplore.ieee.org/document/8047238/
work_keys_str_mv AT hongchunsun improvedsingularvaluedecompositiontopsvdforsourcenumberestimationoflowsnrinblindsourceseparation
AT jingzhengguo improvedsingularvaluedecompositiontopsvdforsourcenumberestimationoflowsnrinblindsourceseparation
AT liangfang improvedsingularvaluedecompositiontopsvdforsourcenumberestimationoflowsnrinblindsourceseparation
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