A modified inertial proximal gradient method for minimization problems and applications

Suparat Kesornprom; Prasit Cholamjiak; Suparat Kesornprom; Prasit Cholamjiak

doi:10.3934/math.2022453

AIMS Mathematics

2022, Volume 7, Issue 5: 8147-8161. doi: 10.3934/math.2022453

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A modified inertial proximal gradient method for minimization problems and applications

Suparat Kesornprom ,
Prasit Cholamjiak ^,

School of Science, University of Phayao, Phayao, Thailand

Received: 17 November 2021 Revised: 20 January 2022 Accepted: 08 February 2022 Published: 24 February 2022
MSC : 65K05, 90C25, 90C30

In this paper, the aim is to design a new proximal gradient algorithm by using the inertial technique with adaptive stepsize for solving convex minimization problems and prove convergence of the iterates under some suitable assumptions. Some numerical implementations of image deblurring are performed to show the efficiency of the proposed methods.
- convex minimization problem,
- forward-backward method,
- adaptive stepsize,
- inertial method,
- weak convergence
Citation: Suparat Kesornprom, Prasit Cholamjiak. A modified inertial proximal gradient method for minimization problems and applications[J]. AIMS Mathematics, 2022, 7(5): 8147-8161. doi: 10.3934/math.2022453

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Abstract

In this paper, the aim is to design a new proximal gradient algorithm by using the inertial technique with adaptive stepsize for solving convex minimization problems and prove convergence of the iterates under some suitable assumptions. Some numerical implementations of image deblurring are performed to show the efficiency of the proposed methods.

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