Regularization Algorithms for Ill-Posed Problems (Hardcover)

This specialized and authoritative book contains an overview of modern approaches to constructing approximations to solutions of ill-posed operator equations, both linear and nonlinear. These approximation schemes form a basis for implementable numerical algorithms for the stable solution of operator equations arising in contemporary mathematical modeling, and in particular when solving inverse problems of mathematical physics. The book presents in detail stable solution methods for ill-posed problems using the methodology of iterative regularization of classical iterative schemes and the techniques of finite dimensional and finite difference approximations of the problems under study. Special attention is paid to ill-posed Cauchy problems for linear operator differential equations and to ill-posed variational inequalities and optimization problems. The readers are expected to have basic knowledge in functional analysis and differential equations. The book will be of interest to applied mathematicians and specialists in mathematical modeling and inverse problems, and also to advanced students in these fields. Contents Introduction Regularization Methods For Linear Equations Finite Difference Methods Iterative Regularization Methods Finite-Dimensional Iterative Processes Variational Inequalities and Optimization Problems

General

Imprint:	De Gruyter
Country of origin:	Germany
Series:	Inverse and Ill-Posed Problems Series
Release date:	February 2018
First published:	2018
Authors:	Anatoly B. Bakushinsky • Mikhail M Kokurin • Mikhail Yu Kokurin
Dimensions:	240 x 170 x 23mm (L x W x T)
Format:	Hardcover - Cloth over boards
Pages:	342
ISBN-13:	978-3-11-055630-8
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Science & Mathematics > Mathematics > Algebra > General Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Functional analysis Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Vector & tensor analysis Books > Science & Mathematics > Mathematics > Applied mathematics > General Promotions
LSN:	3-11-055630-8
Barcode:	9783110556308

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