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| Signal denoising method based on matrix rank minimization and statistical modification |

主管區(qū)長(zhǎng) (文壇精英)
小木蟲(chóng)浪漫體驗(yàn)師~\(^o^)/~
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專家經(jīng)驗(yàn): +790 |
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Accession number: 20153801299470 |

主管區(qū)長(zhǎng) (文壇精英)
小木蟲(chóng)浪漫體驗(yàn)師~\(^o^)/~
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專家經(jīng)驗(yàn): +790 |
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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. |

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