Block-sparse compressed sensing: non-convex model and iterative re-weighted algorithm
نویسندگان
چکیده
Compressed sensing is a new sampling technique which can exactly reconstruct sparse signal from a few measurements. In this article, we consider the blocksparse compressed sensing with special structure assumption about the signal. A novel non-convex model is proposed to reconstruct the block-sparse signals. In addition, the conditions of the proposed model for recovering the block-sparse noise or noise-free signals are presented. The experimental results demonstrate that the proposed non-convex method surpasses the convex method (the mixed ‘2=‘1-norm optimization) and some algorithms without considering the blocksparse structure (the ‘1and ‘p-norm optimization).
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