Name
Abstract | ||
|---|---|---|
The convergence and numerical analysis of a low memory implementation of the Orthogonal Matching Pursuit greedy strategy, which is termed Self Projected Matching Pursuit, is presented. This approach renders an iterative way of solving the least squares problem with much less storage requirement than direct linear algebra techniques. Hence, it is appropriate for solving large linear systems. The analysis highlights its suitability within the class of well posed problems. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.jfranklin.2020.06.006 | Journal of the Franklin Institute |
DocType | Volume | Issue |
Journal | 357 | 13 |
ISSN | Citations | PageRank |
0016-0032 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laura Rebollo-Neira | 1 | 0 | 0.68 |
| Miroslav Rozložník | 2 | 0 | 0.34 |
| Pradip Sasmal | 3 | 0 | 0.34 |