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Solutions of Fixed Point Problems with Computational Errors de Alexander J. Zaslavski

Solutions of Fixed Point Problems with Computational Errors: Springer Optimization and Its Applications

Autor Alexander J. Zaslavski
en Limba Engleză Paperback – 6 apr 2025
The goal is to show the convergence of algorithms, which are known as important tools for solving convex feasibility problems and common fixed point problems.The text also presents studies of algorithms based on unions of nonexpansive maps, inconsistent convex feasibility problems, and split common fixed point problems.
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Specificații

ISBN-13: 9783031508813
ISBN-10: 3031508815
Pagini: 396
Dimensiuni: 155 x 235 x 22 mm
Greutate: 0.6 kg
Editura: Springer
Seria Springer Optimization and Its Applications

Cuprins

1 - Introduction.- 2 - Iterative methods in a Hilbert space.- 3 - The Cimmino algorithm in a Hilbert space.- 4 - Dynamic string-averaging methods in Hilbert spaces.- 5 - Methods with remotest set control in a Hilbert space.- 6 - Algorithms based on unions of nonexpansive maps.- 7 - Inconsistent convex feasibility problems.- 8 - Split common fixed point problems.

Notă biografică

Alexander J. Zaslavski, Department of Mathematics, Technion – Israel Institute of Technology, Haifa, Israel.

Textul de pe ultima copertă

The book is devoted to the study of approximate solutions of fixed point problems in the presence of computational errors. It begins with a study of approximate solutions of star-shaped feasibility problems in the presence of perturbations. The goal is to show the convergence of algorithms, which are known as important tools for solving convex feasibility problems and common fixed point problems. The text also presents studies of algorithms based on unions of nonexpansive maps, inconsistent convex feasibility problems, and split common fixed point problems. A number of algorithms are considered for solving convex feasibility problems and common fixed point problems. The book will be of interest for researchers and engineers working in optimization, numerical analysis, and fixed point theory. It also can be useful in preparation courses for graduate students. The main feature of the book which appeals specifically to this audience is the study of the influence of computational errors for several important algorithms used for nonconvex feasibility problems.

Caracteristici

Studies approximate solutions of star-shaped feasibility problems in the presence of perturbations Analyzes approximate solutions of inconsistent convex feasibility problems in a Hilbert space under perturbations Presents solutions of split common fixed point problems in a Hilbert space under perturbations