• 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