ROBUST MATCHING PURSUIT FOR RECOVERY OF GAUSSIAN SPARSE SIGNAL

被引：0

作者：

Chatterjee, Saikat ^{[1
]}

Sundman, Dennis ^{[1
]}

Skoglund, Mikael ^{[1
]}

机构：

[1] KTH Royal Inst Technol, Sch Elect Engn, Commun Theory Lab, S-10044 Stockholm, Sweden

来源：

2011 IEEE DIGITAL SIGNAL PROCESSING WORKSHOP AND IEEE SIGNAL PROCESSING EDUCATION WORKSHOP (DSP/SPE) | 2011年

关键词：

Orthogonal matching pursuit; MMSE estimation; compressive sensing; SUBSPACE APPROACH;

D O I：

暂无

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：

For compressive sensing (CS) recovery of Gaussian sparse signal, we explore the framework of Bayesian linear models to achieve a robust reconstruction performance in the presence of measurement noise. Using a priori statistical knowledge, we develop a minimum mean square error (MMSE) estimation based iterative greedy search algorithm. Through experimental evaluations, we show that the new algorithm provides a robust CS reconstruction performance compared to an existing least square based algorithm.

引用

页码：420 / 424

页数：5

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