03452nam a22005415i 4500 978-3-031-50879-0 DE-He213 20251030111725.0 cr nn 008mamaa 240319s2024 sz | s |||| 0|eng d 9783031508790 978-3-031-50879-0 10.1007/978-3-031-50879-0 doi QA402.5-402.6 PBU bicssc MAT042000 bisacsh PBU thema Zaslavski, Alexander J. author. aut http://id.loc.gov/vocabulary/relators/aut 73210 Solutions of Fixed Point Problems with Computational Errors [electronic resource] / by Alexander J. Zaslavski. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. IX, 386 p. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Springer Optimization and Its Applications, 1931-6836 ; 210 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. 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. Mathematical optimization. 65522 Operator theory. Mathematics Data processing. 65715 Optimization. 65528 Operator Theory. Computational Mathematics and Numerical Analysis. 66073 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031508783 Printed edition: 9783031508806 Printed edition: 9783031508813 Springer Optimization and Its Applications, 1931-6836 ; 210 73211 https://doi.org/10.1007/978-3-031-50879-0 ZDB-2-SMA ZDB-2-SXMS 58395 58395