Name
Abstract | ||
|---|---|---|
This paper proposes an orthogonal matching pursuit (OMP-) based recovering algorithm for compressive sensing problems. This algorithm can significantly improve recovering performance while it can still maintain reasonable computational complexity. Complexity analysis and simulation results are provided for the proposed algorithm and compared with other popular recovering schemes. We observe that the proposed algorithm can significantly improve the exact recovering performance compared to the OMP scheme. Moreover, in the cases with high compressed ratio, the proposed algorithm can even outperform the benchmark performance achieved by the subspace programming and linear programming. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICASSP.2013.6638757 | 2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) |
Keywords | Field | DocType |
Compressed sensing, orthogonal matching pursuit, K-best | Matching pursuit,Mathematical optimization,Subspace topology,Computer science,Iterative method,Linear programming,Compressed sensing,Computational complexity theory | Conference |
ISSN | Citations | PageRank |
1520-6149 | 2 | 0.39 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pu-Hsuan Lin | 1 | 21 | 2.19 |
| Shang-ho Tsai | 2 | 188 | 24.44 |
| Gene C. H. Chuang | 3 | 43 | 4.78 |