WEIGHTED-DAMPED APPROXIMATE MESSAGE PASSING FOR COMPRESSED SENSING

被引：0

作者：

Wang, Shengchu ^{[1
]}

Li, Yunzhou ^{[1
]}

Gao, Zhen ^{[1
]}

Wang, Jing ^{[1
]}

机构：

[1] Tsinghua Univ, Wireless & Mobile Commun R&D Ctr, Beijing 100084, Peoples R China

来源：

2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2013年

关键词：

Approximate Message Passing; Belief Propagation; Compressed Sensing; Tree-reweighted;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

Approximate Message Passing (AMP) simplified from Loopy Belief Propagation (LBP), is an important algorithm for sparse signal reconstruction in Compressed Sensing (CS). To improve the performance of current AMP algorithms, a weighted-damped AMP algorithm (WDAMP) is derived from a weighted version of BP that adopt probability damping technique. Simulation results show that WDAMP outperforms normal AMP for both 1-D and 2-D signal reconstruction. For 1-D signal reconstruction, probability damping brings most of the improvement. For 2-D signal reconstruction, weighting technique makes the major contribution. In summary, WDAMP outperforms conventional AMP.

引用

页码：5865 / 5869

页数：5

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