DocumentCode
1681165
Title
Weighted-damped Approximate Message Passing for compressed sensing
Author
Shengchu Wang ; Yunzhou Li ; Zhen Gao ; Jing Wang
Author_Institution
Wireless & Mobile Commun. R&D Center, Tsinghua Univ., Beijing, China
fYear
2013
Firstpage
5865
Lastpage
5869
Abstract
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.
Keywords
compressed sensing; message passing; probability; signal reconstruction; LBP; WDAMP; compressed sensing; current AMP algorithms; loopy belief propagation; probability damping; sparse signal reconstruction; weighted-damped AMP algorithm; weighted-damped approximate message passing; Approximation algorithms; Belief propagation; Compressed sensing; Damping; Message passing; Signal reconstruction; Signal to noise ratio; Approximate Message Passing; Belief Propagation; Compressed Sensing; Tree-reweighted;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location
Vancouver, BC
ISSN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2013.6638789
Filename
6638789
Link To Document