Generalized reconstruction algorithm for compressed sensing

被引:13
作者
Lei, J. [1 ]
机构
[1] N China Elect Power Univ, Key Lab Condit Monitoring & Control Power Plant E, Minist Educ, Beijing 102206, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金; 国家高技术研究发展计划(863计划);
关键词
SIGNAL RECOVERY; OPTIMIZATION; SEARCH;
D O I
10.1016/j.compeleceng.2011.04.007
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
080201 [机械制造及其自动化];
摘要
Compressed sensing (CS) is considered as a promising signal processing technique, and successful applications of the CS theory depend mainly on the accuracy and speed of the reconstruction algorithms. In this paper, a generalized objective functional, which has been developed using the combinational estimation and an extended stabilizing functional, is proposed. An efficient iterative scheme, which integrates the beneficial advantages of the homotopy method, the shuffled frog-leaping (SFL) algorithm and the harmony search (HS) algorithm, is designed for searching a possible global optimal solution. Numerical simulations are implemented to evaluate the numerical performances and effectiveness of the proposed algorithm. Excellent numerical performances and encouraging results are observed. For the cases considered in this paper, a dramatic improvement in the reconstruction accuracy is achieved, which indicates that the proposed algorithm is a promising candidate for solving CS inverse problem. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:570 / 588
页数:19
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