New inertial forward–backward algorithm for convex minimization with applications
Abstract: In this work, we present a new proximal gradient algorithm based on Tseng’s extragradient method and an inertial technique to solve the convex minimization problem in real Hilbert spaces. Using the stepsize rules, the selection of the Lipschitz constant of the gradient of functions is avoided. We then prove the weak convergence theorem and present the numerical experiments for image recovery. The comparative results show that the proposed algorithm has better efficiency than other methods.
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
New inertial forward–backward algorithm for convex minimization with applications ; volume:56 ; number:1 ; year:2023 ; extent:13
Demonstratio mathematica ; 56, Heft 1 (2023) (gesamt 13)
- Creator
-
Kankam, Kunrada
Cholamjiak, Watcharaporn
Cholamjiak, Prasit
- DOI
-
10.1515/dema-2022-0188
- URN
-
urn:nbn:de:101:1-2023021613042549225395
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:47 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Kankam, Kunrada
- Cholamjiak, Watcharaporn
- Cholamjiak, Prasit
Other Objects (12)
An accelerated viscosity forward-backward splitting algorithm with the linesearch process for convex minimization problems
An inertial forward-backward method for solving vector optimization problems
Stochastic relaxed inertial forward-backward-forward splitting for monotone inclusions in Hilbert spaces
The forward–backward splitting methods for variational inequalities and minimization problems in Banach spaces
Two-step inertial forward–reflected–anchored–backward splitting algorithm for solving monotone inclusion problems
Convergence of an asynchronous block-coordinate forward-backward algorithm for convex composite optimization
On convergence and complexity analysis of an accelerated forward–backward algorithm with linesearch technique for convex minimization problems and applications to data prediction and classification
Extragradient method for convex minimization problem
Convex minimization and phase field models
Looking backward and looking forward
Dynamical approaches to linearly constrained convex minimization
Convex analysis and minimization algorithms, 1.. Fundamentals
An accelerated viscosity forward-backward splitting algorithm with the linesearch process for convex minimization problems
An inertial forward-backward method for solving vector optimization problems
Stochastic relaxed inertial forward-backward-forward splitting for monotone inclusions in Hilbert spaces
The forward–backward splitting methods for variational inequalities and minimization problems in Banach spaces
Two-step inertial forward–reflected–anchored–backward splitting algorithm for solving monotone inclusion problems
Convergence of an asynchronous block-coordinate forward-backward algorithm for convex composite optimization
On convergence and complexity analysis of an accelerated forward–backward algorithm with linesearch technique for convex minimization problems and applications to data prediction and classification
Extragradient method for convex minimization problem
Convex minimization and phase field models
Looking backward and looking forward
Dynamical approaches to linearly constrained convex minimization
Convex analysis and minimization algorithms, 1.. Fundamentals
An accelerated viscosity forward-backward splitting algorithm with the linesearch process for convex minimization problems
An inertial forward-backward method for solving vector optimization problems
Stochastic relaxed inertial forward-backward-forward splitting for monotone inclusions in Hilbert spaces
The forward–backward splitting methods for variational inequalities and minimization problems in Banach spaces
Two-step inertial forward–reflected–anchored–backward splitting algorithm for solving monotone inclusion problems
Convergence of an asynchronous block-coordinate forward-backward algorithm for convex composite optimization
On convergence and complexity analysis of an accelerated forward–backward algorithm with linesearch technique for convex minimization problems and applications to data prediction and classification
Extragradient method for convex minimization problem
Convex minimization and phase field models
Looking backward and looking forward
Dynamical approaches to linearly constrained convex minimization