A proximal gradient method with double inertial steps for minimization problems involving demicontractive mappings

DOI10.1186/s13660-024-03145-xzbMATH Open1546.90294MaRDI QIDQ6609596

Wipawinee Chaiwino, Raweerote Suparatulatorn, T. Mouktonglang

Publication date: 24 September 2024

Published in: Journal of Inequalities and Applications (Search for Journal in Brave)

zbMATH Keywords

signal recoveryMann iterationprocess innovationproximal gradient method

Mathematics Subject Classification ID

Iterative procedures involving nonlinear operators (47J25) Methods of reduced gradient type (90C52)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• Convergence theorems for inertial KM-type algorithms
• Ergodic convergence to a zero of the sum of monotone operators in Hilbert space
• A logarithmic-quadratic proximal method for variational inequalities
• General inertial Mann algorithms and their convergence analysis for nonexpansive mappings
• Weak convergence of iterative methods for solving quasimonotone variational inequalities
• Generating Nesterov's accelerated gradient algorithm by using optimal control theory for optimization
• Fixed points of nonlinear operators. Iterative methods
• Mean Value Methods in Iteration
• Convex analysis and monotone operator theory in Hilbert spaces
• Nesterov's acceleration for level set-based topology optimization using reaction-diffusion equations
• A parallel method for common variational inclusion and common fixed point problems with applications
• Forward-backward-forward algorithms involving two inertial terms for monotone inclusions

This page was built for publication: A proximal gradient method with double inertial steps for minimization problems involving demicontractive mappings