Analysis of the self projected matching pursuit algorithm

0531904 - MÚ 2021 RIV GB eng J - Journal Article
Rebollo-Neira, L. - Rozložník, Miroslav - Sasmal, P.
Analysis of the self projected matching pursuit algorithm.
Journal of the Franklin Institute-Engineering and Applied Mathematics. Roč. 357, č. 13 (2020), s. 8980-8994. ISSN 0016-0032. E-ISSN 1879-2693
R&D Projects: GA ČR(CZ) GA20-01074S
Institutional support: RVO:67985840
Keywords : linear algebra * Greedy strategies * least squares problems * low memory
OECD category: Applied mathematics
Impact factor: 4.504, year: 2020
Method of publishing: Limited access
https://doi.org/10.1016/j.jfranklin.2020.06.006

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.
Permanent Link: http://hdl.handle.net/11104/0310535