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Springer Algorithms for Common Fixed Point Problems - Vol 132

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Description

This Springer monograph provides a detailed study of approximate solutions for common fixed point problems and convex feasibility problems. Designed for researchers and professionals, the text examines these challenges in the presence of perturbations. Convex feasibility problems involve searching for a common point within a finite collection of subsets in a Hilbert space, while common fixed point problems focus on finding a common fixed point for a finite collection of self-mappings in a Hilbert space. This book explores a variety of algorithms used to solve both types of problems, addressing a rapidly growing area of research. It provides timely insights with numerous applications relevant to the field of engineering.

Key Features

This Springer publication covers approximate solutions to common fixed point problems and convex feasibility problems.

The text analyzes these mathematical problems specifically in the presence of perturbations.

It includes a variety of algorithms designed to solve both common fixed point and convex feasibility problems.

This volume is part of the Springer Optimization and Its Applications series, number 132.

The content highlights numerous applications for engineering and related research fields.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
14 May 2018
Listed Since
07 February 2018

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