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Modified proximal gradient methods involving double inertial extrapolations for monotone inclusion.
- Source :
-
Mathematical Methods in the Applied Sciences . Apr2024, p1. 17p. 9 Illustrations, 6 Charts. - Publication Year :
- 2024
-
Abstract
- In this work, we propose a novel class of forward‐backward‐forward algorithms for solving monotone inclusion problems. Our approach incorporates a self‐adaptive technique to eliminate the need for explicitly selecting Lipschitz assumptions and utilizes two‐step inertial extrapolations to enhance the convergence rate of the algorithm. We establish a weak convergence theorem under mild assumptions. Furthermore, we conduct numerical tests on image deblurring and data classification as practical applications. The experimental results demonstrate that our algorithm surpasses some existing methods in the literature which shows its superior performance and effectiveness. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01704214
- Database :
- Academic Search Index
- Journal :
- Mathematical Methods in the Applied Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 176889567
- Full Text :
- https://doi.org/10.1002/mma.10159