Name
Title | ||
|---|---|---|
Performance Analysis of Approximate Message Passing for Distributed Compressed Sensing. |
Abstract | ||
|---|---|---|
Bayesian approximate message passing (BAMP) is an efficient method in compressed sensing that is nearly optimal in the minimum mean squared error (MMSE) sense. Multiple measurement vector (MMV)-BAMP performs joint recovery of multiple vectors with identical support and accounts for correlations in the signal of interest and in the noise. In this paper, we show how to reduce the complexity of vecto... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/JSTSP.2018.2850754 | IEEE Journal of Selected Topics in Signal Processing |
Keywords | DocType | Volume |
Covariance matrices,Signal processing algorithms,Correlation,Message passing,Noise measurement,Decorrelation,Compressed sensing | Journal | 12 |
Issue | ISSN | Citations |
5 | 1932-4553 | 2 |
PageRank | References | Authors |
0.43 | 18 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gabor Hannak | 1 | 14 | 4.83 |
| Alessandro Perelli | 2 | 19 | 4.83 |
| Norbert Goertz | 3 | 316 | 28.94 |
| Gerald Matz | 4 | 966 | 87.40 |
| Mike E. Davies | 5 | 1664 | 120.39 |