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A New Inertial Self-adaptive Gradient Algorithm for the Split Feasibility Problem and an Application to the Sparse Recovery Problem.
- Source :
-
Acta Mathematica Sinica . Dec2023, Vol. 39 Issue 12, p2489-2506. 18p. - Publication Year :
- 2023
-
Abstract
- In this paper, by combining the inertial technique and the gradient descent method with Polyak's stepsizes, we propose a novel inertial self-adaptive gradient algorithm to solve the split feasibility problem in Hilbert spaces and prove some strong and weak convergence theorems of our method under standard assumptions. We examine the performance of our method on the sparse recovery problem beside an example in an infinite dimensional Hilbert space with synthetic data and give some numerical results to show the potential applicability of the proposed method and comparisons with related methods emphasize it further. [ABSTRACT FROM AUTHOR]
- Subjects :
- *HILBERT space
*SELF-adaptive software
*ORTHOGONAL matching pursuit
*ALGORITHMS
Subjects
Details
- Language :
- English
- ISSN :
- 14398516
- Volume :
- 39
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Acta Mathematica Sinica
- Publication Type :
- Academic Journal
- Accession number :
- 174096192
- Full Text :
- https://doi.org/10.1007/s10114-023-2311-7