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
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;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
DOI :
10.1109/ICASSP.2013.6638789