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
收藏
页码：5865 / 5869
页数：5
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