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Journal Articles IEEE Signal Processing Letters Year : 2010

Compressive Sensing with Chaotic Sequence


Compressive sensing is a new methodology to cap- ture signals at sub-Nyquist rate. To guarantee exact recovery from compressed measurements, one should choose specific matrix, which satisfies the Restricted Isometry Property (RIP), to implement the sensing procedure. In this letter, we propose to construct the sensing matrix with chaotic sequence following a trivial method and prove that with overwhelming probability, the RIP of this kind of matrix is guaranteed. Meanwhile, its experimental comparisons with Gaussian random matrix, Bernoulli random matrix and sparse matrix are carried out and show that the performances among these sensing matrix are almost equal.
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inria-00530058 , version 1 (29-10-2010)



Lei Yu, Jean-Pierre Barbot, Gang Zheng, Hong Sun. Compressive Sensing with Chaotic Sequence. IEEE Signal Processing Letters, 2010, 17 (8), pp.731 - 734. ⟨10.1109/LSP.2010.2052243⟩. ⟨inria-00530058⟩
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