Name
Abstract | ||
|---|---|---|
Practically, in the underdetermined model Y = AX, where X is a K-group sparse matrix (i.e., it has no more than K nonzero rows), both Y and A could be totally perturbed. In this paper, based on restricted isometry property, for the greedy block coordinate descent algorithm, a sufficient condition of exact recovery is presented under the total perturbations, to guarantee that the support of the sparse matrix X is recovered exactly. It is pointed out that there exists some case satisfying our condition, but not the mutual coherence condition. We also discuss the upper bound of our sufficient condition. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/LSP.2014.2307116 | IEEE Signal Process. Lett. |
Keywords | Field | DocType |
coordinate descent algorithm,compressed sensing,perturbation techniques,sparse matrices,k-group sparse matrix,underdetermined model,greedy block coordinate descent,perturbation analysis,greedy algorithms,greedy block algorithm,restricted isometry property,perturbation,indexes,vectors,upper bound,coherence | Discrete mathematics,Mathematical optimization,Combinatorics,Underdetermined system,Perturbation theory,Upper and lower bounds,Greedy algorithm,Coordinate descent,Mathematics,Mutual coherence,Restricted isometry property,Sparse matrix | Journal |
Volume | Issue | ISSN |
21 | 5 | 1070-9908 |
Citations | PageRank | References |
2 | 0.37 | 11 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haifeng Li | 1 | 25 | 7.92 |
| Yuli Fu | 2 | 200 | 29.90 |
| Rui Hu | 3 | 97 | 15.98 |
| Rong Rong | 4 | 12 | 3.66 |