|
|
Title: Signal denoising method based on matrix rank minimization and statistical modification
Authors: Li, Wen-Feng1, 2; Xu, Ai-Qiang1 Email author 253710081@qq.com; Dai, Hao-Min1; Wang, Feng3
Author affiliation: 1 Research Department, Naval Aeronautical and Astronautical University, Yantai, China
2 No. 92635 Unit of PLA, Qingdao, China
3 No. 91206 Unit of PLA, Naval Aeronautical and Astronautical University, Qingdao, China
Corresponding author: Xu, Ai-Qiang
Source title: Zhendong yu Chongji/Journal of Vibration and Shock
Abbreviated source title: J Vib Shock
Volume: 34
Issue: 15
Issue date: August 15, 2015
Publication year: 2015
Pages: 38-44
Language: Chinese
ISSN: 10003835
Document type: Journal article (JA)
Publisher: Chinese Vibration Engineering Society
Abstract: Aiming at the selection problem of effective ranks in singular value decomposition for signal denoising, a signal denoising method based on matrix rank minimization and statistical modification was proposed. Firstly, the effective rank selection problem of singular value decomposition was transformed into a constrained optimization problem of rank by using the matrix rank minimization theory. Secondly, Hankel matrix of a clean signal was obtained with a convex optimization to realize the first noise reduction. At last, the statistical correction was performed for the clean signal's Hankel matrix with subset standard deviation of a singular value to further optimize the noise reduction effect. The simulated signal and real signal test results showed that the method can effectively eliminate pulse noise and Gaussian noise; at the same time, the method can reduce the maximum signal mean square error and improve the signal-to-noise ratio; so the method can enhance the universality of singular value decomposition in signal denoising. ©, 2015, Chinese Vibration Engineering Society. All right reserved.
Number of references: 15
Main heading: Signal denoising
Controlled terms: Constrained optimization - Convex optimization - Gaussian noise (electronic) - Matrix algebra - Mean square error - Optimization - Perturbation techniques - Signal processing - Signal to noise ratio - Singular value decomposition - Statistics
Uncontrolled terms: Constrained optimi-zation problems - Matrix perturbation theory - Matrix rank minimizations - Noise reduction effect - Selection problems - Simulated signals - Singular values - Standard deviation
Classification code: 713 Electronic Circuits - 716 Telecommunication; Radar, Radio and Television - 716.1 Information Theory and Signal Processing - 921 Mathematics - 922.2 Mathematical Statistics - 961 Systems Science
DOI: 10.13465/j.cnki.jvs.2015.15.008
Database: Compendex
Compilation and indexing terms, © 2015 Elsevier Inc. |
|
回复此楼
