Optimal Methods for Ill-Posed Problems

Optimal Methods for Ill-Posed Problems PDF

Author: Vitalii P. Tanana

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2018-03-19

Total Pages: 138

ISBN-13: 3110575833

DOWNLOAD EBOOK →

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

Optimal Methods for Ill-Posed Problems

Optimal Methods for Ill-Posed Problems PDF

Author: Vitalii P. Tanana

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2018-03-19

Total Pages: 138

ISBN-13: 3110577216

DOWNLOAD EBOOK →

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

Regularization Algorithms for Ill-Posed Problems

Regularization Algorithms for Ill-Posed Problems PDF

Author: Anatoly B. Bakushinsky

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2018-02-05

Total Pages: 342

ISBN-13: 3110556383

DOWNLOAD EBOOK →

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 Methods for Ill-Posed Problems

Iterative Methods for Ill-Posed Problems PDF

Author: Anatoly B. Bakushinsky

Publisher: Walter de Gruyter

Published: 2010-12-23

Total Pages: 153

ISBN-13: 3110250659

DOWNLOAD EBOOK →

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 PDF

Author: V.A. Morozov

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 275

ISBN-13: 1461252806

DOWNLOAD EBOOK →

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.

Ill-Posed Problems: Theory and Applications

Ill-Posed Problems: Theory and Applications PDF

Author: A. Bakushinsky

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 268

ISBN-13: 9401110263

DOWNLOAD EBOOK →

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 Regularization Methods for Nonlinear Ill-Posed Problems

Iterative Regularization Methods for Nonlinear Ill-Posed Problems PDF

Author: Barbara Kaltenbacher

Publisher: Walter de Gruyter

Published: 2008-09-25

Total Pages: 205

ISBN-13: 311020827X

DOWNLOAD EBOOK →

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 Methods for Ill-Posed Optimal Control Problems

Regularization Methods for Ill-Posed Optimal Control Problems PDF

Author: Frank Pörner

Publisher: BoD – Books on Demand

Published: 2018-10-04

Total Pages: 181

ISBN-13: 3958260861

DOWNLOAD EBOOK →

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.

Computational Methods for Applied Inverse Problems

Computational Methods for Applied Inverse Problems PDF

Author: Yanfei Wang

Publisher: Walter de Gruyter

Published: 2012-10-30

Total Pages: 552

ISBN-13: 3110259052

DOWNLOAD EBOOK →

Nowadays inverse problems and applications in science and engineering represent an extremely active research field. The subjects are related to mathematics, physics, geophysics, geochemistry, oceanography, geography and remote sensing, astronomy, biomedicine, and other areas of applications. This monograph reports recent advances of inversion theory and recent developments with practical applications in frontiers of sciences, especially inverse design and novel computational methods for inverse problems. The practical applications include inverse scattering, chemistry, molecular spectra data processing, quantitative remote sensing inversion, seismic imaging, oceanography, and astronomical imaging. The book serves as a reference book and readers who do research in applied mathematics, engineering, geophysics, biomedicine, image processing, remote sensing, and environmental science will benefit from the contents since the book incorporates a background of using statistical and non-statistical methods, e.g., regularization and optimization techniques for solving practical inverse problems.