Name
Abstract | ||
|---|---|---|
In this paper, by generalizing the notion of restricted p-isometry constant (0<p≤1) defined by Chartrand and Staneva [1] to the setting of block-sparse signal recovery, we establish a general restricted p-isometry property (p-RIP) condition for recovery of (nearly) block-sparse signals via mixed l2/lp-minimization. Moreover, we derive a lower bound on the necessary number of Gaussian measurements for the p-RIP condition to hold with high probability, which shows clearly that fewer measurements with smaller p are needed for exact recovery of block-sparse signals via mixed l2/lp-minimization than when p=1. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.sigpro.2014.03.040 | Signal Processing |
Keywords | Field | DocType |
Compressed sensing,Block-sparse signal recovery,Mixed l2/lp-minimization,Restricted p-isometry properties,Gaussian measurements | Discrete mathematics,Mathematical optimization,Combinatorics,Generalization,Upper and lower bounds,Isometry,Signal recovery,Minification,Gaussian,Compressed sensing,Restricted isometry property,Mathematics | Journal |
Volume | ISSN | Citations |
104 | 0165-1684 | 5 |
PageRank | References | Authors |
0.42 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yao Wang | 1 | 55 | 3.55 |
| Jianjun Wang | 2 | 53 | 11.84 |
| Zongben Xu | 3 | 3203 | 198.88 |