Name
Abstract | ||
|---|---|---|
•A novel diffusion adaptation framework and two simple yet efficient sparsity adaptive diffusion algorithms are proposed for CS reconstruction.•Novel analyses on convergence conditions and improvement of the step size upper bound are proposed.•Experimental results confirm the theoretical analysis, and show that the proposed diffusion algorithms can achieve desirable reconstruction accuracy as well as much faster convergence speed compared with stand-alone l0-LMS algorithm. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.sigpro.2020.107660 | Signal Processing |
Keywords | DocType | Volume |
Compressive sensing,Diffusion adaptation,Distributed optimization,Sparse signal processing | Journal | 176 |
ISSN | Citations | PageRank |
0165-1684 | 1 | 0.43 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yicong He | 1 | 1 | 1.11 |
| Fei Wang | 2 | 24 | 8.25 |
| Shiyuan Wang | 3 | 2 | 1.46 |
| Badong Chen and Nanning Zheng | 4 | 619 | 50.74 |