An Orthogonal Matching Pursuit Algorithm Based on Singular Value Decomposition

被引：7
|
作者：
Zhang, Cui-juan [1 ]
机构：
[1] Anqing Normal Univ, Univ Key Lab Intelligent Percept & Comp Anhui Pro, Sch Comp & Informat, Anqing 246011, Peoples R China
来源：
CIRCUITS SYSTEMS AND SIGNAL PROCESSING | 2020年 / 39卷 / 01期
关键词：
Compressive sensing; Sparse prior; Singular value decomposition; Orthogonal matching pursuit algorithm; SIGNAL RECOVERY;
D O I：
10.1007/s00034-019-01182-2
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：
A recovery algorithm is one of the most important components in compressive sensing. It is responsible for the recovery of sparse coefficients in some bases of the original signal from a set of non-adaptive and underdetermined linear measurements, and it is a key link between the front-end signal sensing system and back-end processing. In this study, an improved orthogonal matching pursuit algorithm based on singular value decomposition is proposed to overcome the limitations of existing algorithms, which effectively eliminates the correlation between the measured values. The results of simulation experiments show that the proposed algorithm significantly improves the average signal-to-noise ratio, and it performs more robustly than the classical orthogonal matching pursuit algorithm.
引用
收藏
页码：492 / 501
页数：10
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