Bounded perturbations resilient iterative methods for linear systems and least squares problems: operator-based approaches, analysis, and performance evaluation
DOI10.1007/s10543-024-01015-yOpenAlexW4392471271MaRDI QIDQ6204557
Touraj Nikazad, Mokhtar Abbasi
Publication date: 28 March 2024
Published in: BIT (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10543-024-01015-y
inverse problemsleast squares problemsconvex constraintstomographic imagingsemi-convergencesuperiorization methodology
Contraction-type mappings, nonexpansive mappings, (A)-proper mappings, etc. (47H09) Iterative numerical methods for linear systems (65F10) Perturbations of nonlinear operators (47H14) Numerical methods for inverse problems for integral equations (65R32) Fixed-point iterations (47J26)
Cites Work
- Unnamed Item
- Error minimizing relaxation strategies in Landweber and Kaczmarz type iterations
- Convergence and perturbation resilience of dynamic string-averaging projection methods
- Projected subgradient minimization versus superiorization
- AIR tools II: algebraic iterative reconstruction methods, improved implementation
- A new step size rule for the superiorization method and its application in computerized tomography
- The Mathematics of Computerized Tomography
- Weak and Strong Superiorization: Between Feasibility-Seeking and Minimization
- Convergence of string-averaging method for a class of operators
- Multicore Performance of Block Algebraic Iterative Reconstruction Methods
- Perturbation-Resilient Iterative Methods with an Infinite Pool of Mappings
- Stable Convergence Theorems for Infinite Products and Powers of Nonexpansive Mappings
- Perturbation resilience and superiorization of iterative algorithms
- Incremental Subgradients for Constrained Convex Optimization: A Unified Framework and New Methods
- Rank-Deficient and Discrete Ill-Posed Problems
- Total variation superiorized conjugate gradient method for image reconstruction
- Perturbed fixed point iterative methods based on pattern structure
- Discrete Inverse Problems
- A new convergence analysis and perturbation resilience of some accelerated proximal forward–backward algorithms with errors
- A unified treatment of some perturbed fixed point iterative methods with an infinite pool of operators
- Can linear superiorization be useful for linear optimization problems?
- Fast Nonnegative Least Squares Through Flexible Krylov Subspaces
- An Iteration Formula for Fredholm Integral Equations of the First Kind
This page was built for publication: Bounded perturbations resilient iterative methods for linear systems and least squares problems: operator-based approaches, analysis, and performance evaluation