Recovery of Sparse Signal and Nonconvex Minimization

被引：0

作者：

Jing, Jia ^{[1
]}

Wang, Jianjun ^{[1
]}

机构：

[1] Southwest Univ, Sch Math & Stat, Chongqing 400715, Peoples R China

来源：

MATERIAL SCIENCE, CIVIL ENGINEERING AND ARCHITECTURE SCIENCE, MECHANICAL ENGINEERING AND MANUFACTURING TECHNOLOGY II | 2014年 / 651-653卷

关键词：

Sparse signal; Recovery; Compressed sensing; l(q)-minimization; RECONSTRUCTION;

D O I：

10.4028/www.scientific.net/AMM.651-653.2177

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

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 l(q) -minimization, especially for nonconvex case 0<q<1. Using RIP condition, we present sufficient conditions delta((1+c/2)s) +a delta(s) < 1 to guarantee perfect recovery of sparse signal in the noiseless case and stable recovery in the noisy case via l(q) -minimization.

引用

页码：2177 / 2180

页数：4

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