| 期刊全稱(chēng) | Algorithms for Solving Common Fixed Point Problems | | 影響因子2023 | Alexander J. Zaslavski | | 視頻video | http://file.papertrans.cn/154/153249/153249.mp4 | | 發(fā)行地址 | Examines approximate solutions to common fixed point problems.Offers a number of algorithms to solve convex feasibility problems and common fixed point problems.Covers theoretical achievements and app | | 學(xué)科分類(lèi) | Springer Optimization and Its Applications | | 圖書(shū)封面 |  | | 影響因子 | .This book details approximate solutions to common fixed point problems and convex feasibility problems in the presence of perturbations. Convex feasibility problems search for a common point of a finite collection of subsets in a Hilbert space; common fixed point problems pursue a common fixed point of a finite collection of self-mappings in a Hilbert space. A variety of algorithms are considered in this book for solving both types of problems, ?the study of which has fueled a rapidly growing area of research. This monograph is timely and highlights the numerous applications to engineering, computed tomography, and radiation therapy planning.. .Totaling eight chapters, this book begins with an introduction to foundational material and moves on to examine iterative methods in metric spaces. The dynamic string-averaging methods for common fixed point problems in normed space are analyzed in Chapter 3. Dynamic string methods, for common fixed point problemsin a metric space are introduced and discussed in Chapter 4. Chapter 5 is devoted to the convergence of an abstract version of the algorithm which has been called ?component-averaged row projections (CARP). Chapter 6 studies a prox | | Pindex | Book 2018 |
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