Optimal Methods for Ill-Posed Problems

Optimal Methods for Ill-Posed Problems
Author: Vitalii P. Tanana
Publisher: Walter de Gruyter GmbH & Co KG
Total Pages: 138
Release: 2018-03-19
Genre: Mathematics
ISBN: 3110577216

The book covers fundamentals of the theory of optimal methods for solving ill-posed problems, as well as ways to obtain accurate and accurate-by-order error estimates for these methods. The methods described in the current book are used to solve a number of inverse problems in mathematical physics. Contents Modulus of continuity of the inverse operator and methods for solving ill-posed problems Lavrent’ev methods for constructing approximate solutions of linear operator equations of the first kind Tikhonov regularization method Projection-regularization method Inverse heat exchange problems

Iterative Methods for Ill-Posed Problems

Iterative Methods for Ill-Posed Problems
Author: Anatoly B. Bakushinsky
Publisher: Walter de Gruyter
Total Pages: 153
Release: 2010-12-23
Genre: Mathematics
ISBN: 3110250659

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.

Methods for Solving Incorrectly Posed Problems

Methods for Solving Incorrectly Posed Problems
Author: V.A. Morozov
Publisher: Springer Science & Business Media
Total Pages: 275
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461252806

Some problems of mathematical physics and analysis can be formulated as the problem of solving the equation f € F, (1) Au = f, where A: DA C U + F is an operator with a non-empty domain of definition D , in a metric space U, with range in a metric space F. The metrics A on U and F will be denoted by P and P ' respectively. Relative u F to the twin spaces U and F, J. Hadamard P-06] gave the following defini tion of correctness: the problem (1) is said to be well-posed (correct, properly posed) if the following conditions are satisfied: (1) The range of the value Q of the operator A coincides with A F ("sol vabi li ty" condition); (2) The equality AU = AU for any u ,u € DA implies the I 2 l 2 equality u = u ("uniqueness" condition); l 2 (3) The inverse operator A-I is continuous on F ("stability" condition). Any reasonable mathematical formulation of a physical problem requires that conditions (1)-(3) be satisfied. That is why Hadamard postulated that any "ill-posed" (improperly posed) problem, that is to say, one which does not satisfy conditions (1)-(3), is non-physical. Hadamard also gave the now classical example of an ill-posed problem, namely, the Cauchy problem for the Laplace equation.

Regularization Algorithms for Ill-Posed Problems

Regularization Algorithms for Ill-Posed Problems
Author: Anatoly B. Bakushinsky
Publisher: Walter de Gruyter GmbH & Co KG
Total Pages: 447
Release: 2018-02-05
Genre: Mathematics
ISBN: 3110556383

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

Iterative Regularization Methods for Nonlinear Ill-Posed Problems

Iterative Regularization Methods for Nonlinear Ill-Posed Problems
Author: Barbara Kaltenbacher
Publisher: Walter de Gruyter
Total Pages: 205
Release: 2008-09-25
Genre: Mathematics
ISBN: 311020827X

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.

Ill-Posed Problems: Theory and Applications

Ill-Posed Problems: Theory and Applications
Author: A. Bakushinsky
Publisher: Springer Science & Business Media
Total Pages: 268
Release: 2012-12-06
Genre: Mathematics
ISBN: 9401110263

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.

Computational Methods for Inverse Problems

Computational Methods for Inverse Problems
Author: Curtis R. Vogel
Publisher: SIAM
Total Pages: 195
Release: 2002-01-01
Genre: Mathematics
ISBN: 0898717574

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

Regularization Methods for Ill-Posed Optimal Control Problems

Regularization Methods for Ill-Posed Optimal Control Problems
Author: Frank Pörner
Publisher: BoD – Books on Demand
Total Pages: 181
Release: 2018-10-04
Genre: Mathematics
ISBN: 3958260861

Ill-posed optimization problems appear in a wide range of mathematical applications, and their numerical solution requires the use of appropriate regularization techniques. In order to understand these techniques, a thorough analysis is inevitable. The main subject of this book are quadratic optimal control problems subject to elliptic linear or semi-linear partial differential equations. Depending on the structure of the differential equation, different regularization techniques are employed, and their analysis leads to novel results such as rate of convergence estimates.

Regularization of Inverse Problems

Regularization of Inverse Problems
Author: Heinz Werner Engl
Publisher: Springer Science & Business Media
Total Pages: 340
Release: 2000-03-31
Genre: Mathematics
ISBN: 9780792361404

This book is devoted to the mathematical theory of regularization methods and gives an account of the currently available results about regularization methods for linear and nonlinear ill-posed problems. Both continuous and iterative regularization methods are considered in detail with special emphasis on the development of parameter choice and stopping rules which lead to optimal convergence rates.

Numerical Methods for the Solution of Ill-Posed Problems

Numerical Methods for the Solution of Ill-Posed Problems
Author: A.N. Tikhonov
Publisher: Springer Science & Business Media
Total Pages: 257
Release: 2013-03-09
Genre: Mathematics
ISBN: 940158480X

Many problems in science, technology and engineering are posed in the form of operator equations of the first kind, with the operator and RHS approximately known. But such problems often turn out to be ill-posed, having no solution, or a non-unique solution, and/or an unstable solution. Non-existence and non-uniqueness can usually be overcome by settling for `generalised' solutions, leading to the need to develop regularising algorithms. The theory of ill-posed problems has advanced greatly since A. N. Tikhonov laid its foundations, the Russian original of this book (1990) rapidly becoming a classical monograph on the topic. The present edition has been completely updated to consider linear ill-posed problems with or without a priori constraints (non-negativity, monotonicity, convexity, etc.). Besides the theoretical material, the book also contains a FORTRAN program library. Audience: Postgraduate students of physics, mathematics, chemistry, economics, engineering. Engineers and scientists interested in data processing and the theory of ill-posed problems.