Subspace Thresholding Pursuit: A Reconstruction Algorithm for Compressed Sensing

被引：0

作者：

Song, Chao-Bing ^{[1
]}

Xia, Shu-Tao ^{[1
]}

Liu, Xin-Ji ^{[1
]}

机构：

[1] Tsinghua Univ, Grad Sch ShenZhen, Shenzhen 518055, Guangdong, Peoples R China

来源：

2015 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT) | 2015年

关键词：

Compressed sensing; restricted isometry constants; subspace thresholding pursuit; sparse recovery; RECOVERY;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We propose a new iterative greedy algorithm to reconstruct sparse signals in compressed sensing. By a simple combination of subspace pursuit and iterative hard thresholding, the proposed algorithm, called subspace thresholding pursuit (STP) shows well improved empirical performance, while still keeps a strong theoretical guarantee in terms of restricted isometry property.

引用

页码：536 / 540

页数：5

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