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In this paper, a new wavelet packet denoising method based on sparse representation is proposed to remove the noises from WFT signal. In this method, the problem of recovering the noiseless signal is converted into an optimization problem of recovering the sparsity of their wavelet package coefficients, and the wavelet package coefficients of the noiseless signals can be obtained by the augmented Lagrange optimization method. Then the denoised WFT signal can be reconstructed by wavelet packet reconstruction. The experiments on simulation signal and WFT signal show that the proposed denoising method based on sparse representation is more effective for denoising WFT signal than the soft and hard threshold denoising methods.<\/jats:p>","DOI":"10.1155\/2014\/145870","type":"journal-article","created":{"date-parts":[[2014,2,13]],"date-time":"2014-02-13T16:02:30Z","timestamp":1392307350000},"page":"1-10","source":"Crossref","is-referenced-by-count":3,"title":["Denoising Method Based on Sparse Representation for WFT Signal"],"prefix":"10.1155","volume":"2014","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1224-7644","authenticated-orcid":true,"given":"Xu","family":"Chen","sequence":"first","affiliation":[{"name":"School of Information and Control, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8373-3063","authenticated-orcid":true,"given":"Guoyu","family":"Lin","sequence":"additional","affiliation":[{"name":"School 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