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Volume 31 Issue 12
Dec.  2010
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HE Weikun, GUO Shuangshuang, WANG Xiaoliang, WU Renbiao. Weather Radar Wind Farms Clutters Detection and Identification Method Based on Level-II Data and Fuzzy Logic Inference[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3252-3260. doi: 10.11999/JEIT161031
Citation: Guo Hai-yan, Yang Zhen. Compressed Speech Signal Sensing Based on Approximate KLT[J]. Journal of Electronics & Information Technology, 2009, 31(12): 2948-2952. doi: 10.3724/SP.J.1146.2008.01704

Compressed Speech Signal Sensing Based on Approximate KLT

doi: 10.3724/SP.J.1146.2008.01704
  • Received Date: 2008-12-15
  • Rev Recd Date: 2009-05-18
  • Publish Date: 2009-12-19
  • Compressed Sensing is a research focus rising in recent years. On the basis of the signals sparse representation in the KLT domain, this paper proposes an approximate KLT method using template matching and studies on the corresponding compressed speech signal sensing. First, it verifies the sparsity of speech signal in the approximate KLT domain. Second, by speech signal and a measurement matrix, it arranges measurements of fixed or adaptive length according to frame energy. Third, according to the measurements, it finds the speech signals sparsest coefficient vector through L1 optimization algorithm to recover the speech signal. Simulation results demonstrate that compressed speech signal sensing in the approximate KLT using template matching has good performance.
  • Donoho D. Compressed sensing[J].IEEE Transactions onInformation Theory.2006, 52(4):1289-1306[2]Tsaig Y and Donoho D. Extensions of compressed sensing[J].Signal Processing.2006, 86(3):533-548[3]Cands E, Romberg J, and Tao T. Robust uncertaintyprinciples: Exact signal reconstruction from highlyincomplete frequency information[J].IEEE Transactions onInformation Theory.2006, 52(2):489-509[4]Romberg J. Imaging via compressive sampling. IEEE SignalProcessing Magazine, 2008, 25(2): 14-20.[5]Duarte M, Davenport M, Takhar D, Laska J, Sun T, Kelly K,and Baraniuk R. Single-pixel imaging via compressivesampling[J].IEEE Signal Processing Magazine.2008, 25(2):83-91[6]Gemmeke J F and Cranen B. Using sparse representations formissing data imputation in noise robust speech recognition.European Signal Processing Conf. (EUSIPCO), Lausanne,Switzerland, August 2008: 987-991.[7]Baraniuk R G. Compressive sensing. IEEE Signal ProcessingMagazine, 2007, 24(4): 118-121.[8]Baron D, Wakin M, Duarte M, Sarvotham S, and Baraniuk R.Distributed compressed sensing. Technical Report ECE-0612,Electrical and Computer Engineering Department, RiceUniversity, December 2006.[9]Chen S S, Donoho D L, and Saunders M A. Atomicdecomposition by basis pursuit[J].SIAM Review.2001, 43(1):129-159[10]A帕普里斯, SU佩莱著, 保铮, 冯大政, 水鹏朗译. 概率、随机变量与随机过程. 第4 版, 西安: 西安交通大学出版社,2004: 209-213.[11]Coifman R R and Donoho D L. Translation-InvariantDe-noising. New York: Springer-Verlag, 1995: 125-150.
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