Name
Abstract | ||
|---|---|---|
The generalized Orthogonal Matching Pursuit (gOMP) is a recently proposed compressive sensing greedy recovery algorithm which generalizes the OMP algorithm by selecting N(>= 1) atoms in each iteration. In this letter, we demonstrate that the gOMP can successfully reconstruct a K-sparse signal from a compressed measurement y = Phi x by a maximum of K iterations if the sensing matrix Phi satisfies the Restricted Isometry Property (RIP) of order NK, with the RIP constant delta(NK) satisfying delta(NK) < root N/root K+2 root N. The proposed bound is an improvement over the existing bound on delta(NK). We also show that by increasing the RIP order just by one (i.e., NK+1 from NK), it is possible to refine the bound further to delta(NK+1) < root N/root K+root N, which is consistent (for N = 1) with the near optimal bound on delta(K+1) in OMP. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/LSP.2013.2279977 | IEEE SIGNAL PROCESSING LETTERS |
Keywords | Field | DocType |
Compressive sensing, orthogonal matching pursuit, restricted isometry property, sensing matrix | Matching pursuit,Combinatorics,Mathematical optimization,Matrix (mathematics),Iterative method,Greedy algorithm,Compressed sensing,Restricted isometry property,Mathematics,Signal reconstruction | Journal |
Volume | Issue | ISSN |
20 | 11 | 1070-9908 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Siddhartha Satpathi | 1 | 24 | 3.84 |
| Rajib Lochan Das | 2 | 35 | 4.97 |
| Mrityunjoy Chakraborty | 3 | 124 | 28.63 |