Sparse Recovery Based on Transformation Basis of FTT and DWT

1，2Shanxiong Chen, 1 Zhongshi He , 2Hailing Xiong ,2Xianping Yu ,2Xiaoyan liu 1College of Computer Science, Chongqing University, Chongqing, 400030, China 2College of Computer and Information Science, Southwest University, Chongqing ,400716 ,China csxpml@163.com 3Chongqing city management college Chongqing 401331, China

Abstract  When the signal in a transform domain is sparse or compressible ，it could be projected to low-dimensional vector utilizing measurement matrix. This projection maintains the information required by reconstructing signal. By research about the basic theories for compressed sensing, this article adopted FFT and DWT as the transform matrix  respectively, the random matrix as the sampling , then analyzed the coherence among them in addition to the sparsity of the sampling signals, explored further the ability of the two methods for recovering signals.

Keyword  Sparse Recovery; Incoherence; FFT; Reconstructing Signals

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，Shanxiong Chen, Zhongshi He , Hailing Xiong ,Xianping Yu ,Xiaoyan liu, "Sparse Recovery Based on Transformation Basis of FTT and DWT", IJACT: International Journal of Advancements in Computing Technology, Vol. 4, No. 18, pp. 407 ~ 415, 2012