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Signal denoising method based on matrix rank minimization and statistical modification

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Accession number:  
20153801299470
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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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