Optimal Sensing Matrix for Compressed Sensing

被引：0

作者：

Yu, Lifeng ^{[1
]}

Bai, Huang ^{[1
]}

Wan, Xiaofang ^{[1
]}

机构：

[1] Zhejiang Univ Technol, Coll Informat Engn, Hangzhou 310014, Zhejiang, Peoples R China

来源：

2011 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND CONTROL (ICECC) | 2011年

关键词：

compressed sensing; RIP; MIP; optimization; eigenvalue; mutual coherence; SIGNAL RECOVERY; PROJECTIONS;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a novel framework of fast and efficient compressed sampling based on the restricted isometry property (RIP). The proposed framework provides three features. i) It is universal with a variety of sparse signals. ii) The reconstruction errors can be minimized. iii) It has fast computation, that is, it needs few iterations. All currently existing methods don't satisfy these desired features. Experimental results are presented to verify the validity as well as to illustrate the promising potential of the proposed framework.

引用

页码：360 / 363

页数：4

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