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This paper deals with designing sensing matrix for compressive sensing systems. Traditionally, the optimal sensing matrix is designed so that the Gram of the equivalent dictionary is as close as possible to a target Gram with small mutual coherence. A novel design strategy is proposed, in which, unlike the traditional approaches, the measure considers of mutual coherence behavior of the equivalent...
The compressive sensing (CS) theory has shown that sparse signals can be reconstructed exactly from much fewer measurements than traditionally believed. What's more, using ℓp-norm minimization with p < 1 can do so with much fewer measurements than with p=1. In this paper, a novel algorithm is proposed for computing local minima of the nonconvex problem in the block-sparse system. A series of experiments...
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