{"title":"An Efficient Nonconvex Regularization Method for Wavelet Frame Based Compressed Sensing Recovery","authors":"Xiao-Juan Yang, Jin Jing","doi":"10.47260/JCOMOD/1111","DOIUrl":null,"url":null,"abstract":"Abstract\nIn this paper, we propose a variation model which takes advantage of the wavelet\ntight frame and nonconvex shrinkage penalties for compressed sensing recovery.\nWe address the proposed optimization problem by introducing a adjustable\nparameter and a firm thresholding operations. Numerical experiment results show\nthat the proposed method outperforms some existing methods in terms of the\nconvergence speed and reconstruction errors.\n\nJEL classification numbers: 68U10, 65K10, 90C25, 62H35.\nKeywords: Compressed Sensing, Nonconvex, Firm thresholding, Wavelet tight\nframe.","PeriodicalId":30638,"journal":{"name":"International Journal of Mathematical Modelling Computations","volume":"90 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Mathematical Modelling Computations","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47260/JCOMOD/1111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract
In this paper, we propose a variation model which takes advantage of the wavelet
tight frame and nonconvex shrinkage penalties for compressed sensing recovery.
We address the proposed optimization problem by introducing a adjustable
parameter and a firm thresholding operations. Numerical experiment results show
that the proposed method outperforms some existing methods in terms of the
convergence speed and reconstruction errors.
JEL classification numbers: 68U10, 65K10, 90C25, 62H35.
Keywords: Compressed Sensing, Nonconvex, Firm thresholding, Wavelet tight
frame.
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