Open AccessA modified inertial proximal gradient method for minimization problems and applications
Author(s) -
Suparat Kesornprom,
AUTHOR_ID,
Prasit Cholamjiak
Publication year - 2022
Publication title -
aims mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.329
H-Index - 15
ISSN - 2473-6988
DOI - 10.3934/math.2022453
Subject(s) - deblurring , iterated function , minification , inertial frame of reference , convergence (economics) , mathematics , preconditioner , regular polygon , image (mathematics) , computer science , mathematical optimization , algorithm , image restoration , iterative method , image processing , computer vision , geometry , mathematical analysis , physics , quantum mechanics , economic growth , economics
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.