Abstract
In this paper, we present sufficient conditions in term of the restricted isometry property (RIP) to guarantee perfect recovery of sparse signal in the noiseless case and stable recovery in the noisy case via Lq-minimization, especially for nonconvex case 0<q<1. Using RIP condition, we present sufficient conditions to guarantee perfect recovery of sparse signal in the noiseless case and stable recovery in the noisy case via Lq-minimization.
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