Iterative Regularization Methods for Nonlinear Ill-Posed Problems PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Iterative Regularization Methods for Nonlinear Ill-Posed Problems PDF full book. Access full book title Iterative Regularization Methods for Nonlinear Ill-Posed Problems by Barbara Kaltenbacher. Download full books in PDF and EPUB format.

Iterative Regularization Methods for Nonlinear Ill-Posed Problems

Iterative Regularization Methods for Nonlinear Ill-Posed Problems PDF Author: Barbara Kaltenbacher
Publisher: Walter de Gruyter
ISBN: 311020827X
Category : Mathematics
Languages : en
Pages : 205

Book Description
Nonlinear inverse problems appear in many applications, and typically they lead to mathematical models that are ill-posed, i.e., they are unstable under data perturbations. Those problems require a regularization, i.e., a special numerical treatment. This book presents regularization schemes which are based on iteration methods, e.g., nonlinear Landweber iteration, level set methods, multilevel methods and Newton type methods.

Iterative Regularization Methods for Nonlinear Ill-Posed Problems

Iterative Regularization Methods for Nonlinear Ill-Posed Problems PDF Author: Barbara Kaltenbacher
Publisher: Walter de Gruyter
ISBN: 311020827X
Category : Mathematics
Languages : en
Pages : 205

Book Description
Nonlinear inverse problems appear in many applications, and typically they lead to mathematical models that are ill-posed, i.e., they are unstable under data perturbations. Those problems require a regularization, i.e., a special numerical treatment. This book presents regularization schemes which are based on iteration methods, e.g., nonlinear Landweber iteration, level set methods, multilevel methods and Newton type methods.

Regularization Algorithms for Ill-Posed Problems

Regularization Algorithms for Ill-Posed Problems PDF Author: Anatoly B. Bakushinsky
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110556383
Category : Mathematics
Languages : en
Pages : 342

Book Description
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

Regularization of Ill-Posed Problems by Iteration Methods

Regularization of Ill-Posed Problems by Iteration Methods PDF Author: S.F. Gilyazov
Publisher: Springer
ISBN: 9789401594837
Category : Mathematics
Languages : en
Pages : 342

Book Description
Iteration regularization, i.e., utilization of iteration methods of any form for the stable approximate solution of ill-posed problems, is one of the most important but still insufficiently developed topics of the new theory of ill-posed problems. In this monograph, a general approach to the justification of iteration regulari zation algorithms is developed, which allows us to consider linear and nonlinear methods from unified positions. Regularization algorithms are the 'classical' iterative methods (steepest descent methods, conjugate direction methods, gradient projection methods, etc.) complemented by the stopping rule depending on level of errors in input data. They are investigated for solving linear and nonlinear operator equations in Hilbert spaces. Great attention is given to the choice of iteration index as the regularization parameter and to estimates of errors of approximate solutions. Stabilizing properties such as smoothness and shape constraints imposed on the solution are used. On the basis of these investigations, we propose and establish efficient regularization algorithms for stable numerical solution of a wide class of ill-posed problems. In particular, descriptive regularization algorithms, utilizing a priori information about the qualitative behavior of the sought solution and ensuring a substantial saving in computational costs, are considered for model and applied problems in nonlinear thermophysics. The results of calculations for important applications in various technical fields (a continuous casting, the treatment of materials and perfection of heat-protective systems using laser and composite technologies) are given.

Regularization of Ill-Posed Problems by Iteration Methods

Regularization of Ill-Posed Problems by Iteration Methods PDF Author: S.F. Gilyazov
Publisher: Springer Science & Business Media
ISBN: 9401594821
Category : Mathematics
Languages : en
Pages : 348

Book Description
Iteration regularization, i.e., utilization of iteration methods of any form for the stable approximate solution of ill-posed problems, is one of the most important but still insufficiently developed topics of the new theory of ill-posed problems. In this monograph, a general approach to the justification of iteration regulari zation algorithms is developed, which allows us to consider linear and nonlinear methods from unified positions. Regularization algorithms are the 'classical' iterative methods (steepest descent methods, conjugate direction methods, gradient projection methods, etc.) complemented by the stopping rule depending on level of errors in input data. They are investigated for solving linear and nonlinear operator equations in Hilbert spaces. Great attention is given to the choice of iteration index as the regularization parameter and to estimates of errors of approximate solutions. Stabilizing properties such as smoothness and shape constraints imposed on the solution are used. On the basis of these investigations, we propose and establish efficient regularization algorithms for stable numerical solution of a wide class of ill-posed problems. In particular, descriptive regularization algorithms, utilizing a priori information about the qualitative behavior of the sought solution and ensuring a substantial saving in computational costs, are considered for model and applied problems in nonlinear thermophysics. The results of calculations for important applications in various technical fields (a continuous casting, the treatment of materials and perfection of heat-protective systems using laser and composite technologies) are given.

Iterative Methods for Ill-Posed Problems

Iterative Methods for Ill-Posed Problems PDF Author: Anatoly B. Bakushinsky
Publisher: Walter de Gruyter
ISBN: 3110250659
Category : Mathematics
Languages : en
Pages : 153

Book Description
Ill-posed problems are encountered in countless areas of real world science and technology. A variety of processes in science and engineering is commonly modeled by algebraic, differential, integral and other equations. In a more difficult case, it can be systems of equations combined with the associated initial and boundary conditions. Frequently, the study of applied optimization problems is also reduced to solving the corresponding equations. These equations, encountered both in theoretical and applied areas, may naturally be classified as operator equations. The current textbook will focus on iterative methods for operator equations in Hilbert spaces.

Ill-Posed Problems: Theory and Applications

Ill-Posed Problems: Theory and Applications PDF Author: A. Bakushinsky
Publisher: Springer Science & Business Media
ISBN: 9401110263
Category : Mathematics
Languages : en
Pages : 268

Book Description
Recent years have been characterized by the increasing amountofpublications in the field ofso-called ill-posed problems. This is easilyunderstandable because we observe the rapid progress of a relatively young branch ofmathematics, ofwhich the first results date back to about 30 years ago. By now, impressive results have been achieved both in the theory ofsolving ill-posed problems and in the applicationsofalgorithms using modem computers. To mention just one field, one can name the computer tomography which could not possibly have been developed without modem tools for solving ill-posed problems. When writing this book, the authors tried to define the place and role of ill posed problems in modem mathematics. In a few words, we define the theory of ill-posed problems as the theory of approximating functions with approximately given arguments in functional spaces. The difference between well-posed and ill posed problems is concerned with the fact that the latter are associated with discontinuous functions. This approach is followed by the authors throughout the whole book. We hope that the theoretical results will be of interest to researchers working in approximation theory and functional analysis. As for particular algorithms for solving ill-posed problems, the authors paid general attention to the principles ofconstructing such algorithms as the methods for approximating discontinuous functions with approximately specified arguments. In this way it proved possible to define the limits of applicability of regularization techniques.

Iterative Methods for Ill-posed Problems

Iterative Methods for Ill-posed Problems PDF Author: Anatoly B. Bakushinsky
Publisher: Walter de Gruyter
ISBN: 3110250640
Category : Mathematics
Languages : en
Pages : 153

Book Description
Ill-posed problems are encountered in countless areas of real world science and technology. A variety of processes in science and engineering is commonly modeled by algebraic, differential, integral and other equations. In a more difficult case, it can be systems of equations combined with the associated initial and boundary conditions. Frequently, the study of applied optimization problems is also reduced to solving the corresponding equations. These equations, encountered both in theoretical and applied areas, may naturally be classified as operator equations. The current textbook will focus on iterative methods for operator equations in Hilbert spaces.

Handbook of Mathematical Methods in Imaging

Handbook of Mathematical Methods in Imaging PDF Author: Otmar Scherzer
Publisher: Springer Science & Business Media
ISBN: 0387929193
Category : Mathematics
Languages : en
Pages : 1626

Book Description
The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 150 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and computer scientists working in imaging will also find this handbook useful.

Computational Methods for Inverse Problems

Computational Methods for Inverse Problems PDF Author: Curtis R. Vogel
Publisher: SIAM
ISBN: 0898717574
Category : Mathematics
Languages : en
Pages : 195

Book Description
Provides a basic understanding of both the underlying mathematics and the computational methods used to solve inverse problems.

Regularization for Applied Inverse and Ill-Posed Problems

Regularization for Applied Inverse and Ill-Posed Problems PDF Author:
Publisher: Springer-Verlag
ISBN: 3322930343
Category : Technology & Engineering
Languages : de
Pages : 199

Book Description