Sparse Signal Recovery With Minimization of 1-Norm Minus 2-Norm

被引：45

作者：

Wen, Jinming ^{[1
,2
]}

Weng, Jian ^{[1
,2
]}

Tong, Chao ^{[3
]}

Ren, Chao ^{[4
]}

Zhou, Zhengchun ^{[5
]}

机构：

[1] Jinan Univ, Coll Informat Sci & Technol, Guangzhou 510632, Guangdong, Peoples R China

[2] Jinan Univ, Coll Cyber Secur, Guangzhou 510632, Guangdong, Peoples R China

[3] Beihang Univ, Sch Comp Sci & Engn, Beijing 100191, Peoples R China

[4] Univ Sci & Technol Beijing, Beijing Adv Innovat Ctr Mat Genome Engn, Beijing Engn & Technol Res Ctr Convergence Networ, Inst Artificial Intelligence, Beijing 100083, Peoples R China

[5] Southwest Jiaotong Univ, Sch Math, Chengdu 610031, Sichuan, Peoples R China

来源：

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY | 2019年 / 68卷 / 07期

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

Sparse signal recovery; mutual coherence; sufficient condition; CHANNEL ESTIMATION; STABLE RECOVERY;

D O I：

10.1109/TVT.2019.2919612

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The key aim of compressed sensing is to stably recover a K-sparse signals x from a linearmodel y = Ax + v, where v is a noise vector. Minimization of parallel to x parallel to(1) - parallel to x parallel to(2) is a recently proposed effective recovery method. In this paper, we show that if the mutual coherence mu of A satisfies mu < 1/3K, then this method can stably recover any K-sparse signalxbased ony and A. As far as we know, this is the first sufficient condition based on mutual coherence for such method.

引用

页码：6847 / 6854

页数：8

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