Name
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICASSP.2013.6638789 | 2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) |
Keywords | Field | DocType |
Approximate Message Passing, Belief Propagation, Compressed Sensing, Tree-reweighted | Weighting,Pattern recognition,Computer science,Artificial intelligence,Compressed sensing,Message passing,Signal reconstruction,Belief propagation | Conference |
Volume | Issue | ISSN |
null | null | 1520-6149 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shengchu Wang | 1 | 81 | 7.92 |
| Yunzhou Li | 2 | 345 | 36.62 |
| Zhen Gao | 3 | 0 | 0.68 |
| Jing Wang | 4 | 23 | 6.48 |