A double projection algorithm with inertial effects for solving split feasibility problems and applications to image restoration
From MaRDI portal
Publication:5058171
DOI10.23952/jnva.7.2023.1.02OpenAlexW4311162898MaRDI QIDQ5058171
Suthep Suantai, Suparat Kesornprom, Prasit Cholamjiak
Publication date: 19 December 2022
Published in: Journal of Nonlinear and Variational Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.23952/jnva.7.2023.1.02
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- ``Optimal choice of the step length of the projection and contraction methods for solving the split feasibility problem
- A multiprojection algorithm using Bregman projections in a product space
- A relaxed projection method using a new linesearch for the split feasibility problem
- On the convergence analysis of the gradient-CQ algorithms for the split feasibility problem
- A strong convergence theorem for Tseng's extragradient method for solving variational inequality problems
- Modified projection methods for the split feasibility problem and the multiple-sets split feasibility problem
- Double projection algorithms for solving the split feasibility problems
- A new halfspace-relaxation projection method for the split feasibility problem
- The multiple-sets split feasibility problem and its applications for inverse problems
- A unified treatment of some iterative algorithms in signal processing and image reconstruction
- Iterative oblique projection onto convex sets and the split feasibility problem
- The relaxed CQ algorithm solving the split feasibility problem
- Some methods of speeding up the convergence of iteration methods
- A note on the CQ algorithm for the split feasibility problem
- A Weak-to-Strong Convergence Principle for Fejér-Monotone Methods in Hilbert Spaces
- Strong convergence of inertial forward–backward methods for solving monotone inclusions
- Convex analysis and monotone operator theory in Hilbert spaces
- An alternated inertial general splitting method with linearization for the split feasibility problem