Methods for Solving Incorrectly Posed Problems

Author:   V.A. Morozov ,  Z. Nashed ,  A.B. Aries
Publisher:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 1984
ISBN:  

9780387960593


Pages:   257
Publication Date:   20 November 1984
Format:   Paperback
Availability:   Out of stock   Availability explained
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Methods for Solving Incorrectly Posed Problems


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Overview

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.

Full Product Details

Author:   V.A. Morozov ,  Z. Nashed ,  A.B. Aries
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 1984
Dimensions:   Width: 15.50cm , Height: 1.40cm , Length: 23.50cm
Weight:   0.429kg
ISBN:  

9780387960593


ISBN 10:   0387960597
Pages:   257
Publication Date:   20 November 1984
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.
Language:   English & Russian

Table of Contents

1. The Regularization Method.- Section 1. The Basic Problem for Linear Operators.- Section 2. The Approximation of the Solution of the Basic Problem.- Section 3. The Euler Variation Inequality. Estimation of Accuracy.- Section 4. Stability of Regularized Solutions.- Section 5. Approximation of the Admissible Set. Choice of the Basis.- 2. Criteria for Selection of Regularization Parameter.- Section 6. Some Properties of Regularized Solutions.- Section 7. Methods for Choosing the Parameter: Case of Exact Information.- Section 8. The Residual Method and the Method of Quasi-solutions: Case of Exact Information.- Section 9. Properties of the Auxiliary Functions.- Section 10. Criteria for the Choice of a Parameter: Case of Inexact Data.- 3. Regular Methods for Solving Linear and Nonlinear Ill-Posed Problems.- Section 11. Regularity of Approximation Methods.- Section 12. The Theory of Accuracy of Regular Methods.- Section 13. The Computation of the Estimation Function.- Section 14. Examples of Regular Methods.- Section 15. The Principle of Residual Optimality for Approximate Solutions of Equations with Nonlinear Operators.- Section 16. The Regularization Method for Nonlinear Equations.- 4. The Problem of Computation and the General Theory of Splines.- Section 17. The Problem of Computation and the Parameter Identification Problem.- Section 18. Properties of Smoothing Families of Operators.- Section 19. The Optimality of Smoothing Algorithms.- Section 20. The Differentiation Problem and Algorithms of Approximation of the Experimental Data.- Section 21.The Theory of Splines and the Problem of Stable Computation of Values of an Unbounded Operator.- Section 22. Approximate Solution of Operator Equations Using Splines.- Section 23. Recovering the Solution of the Basic Problem From Approximate Values of the Functiona1s.- 5. Regular Methods for Special Cases of the Basic Problem. Algorithms for Choosing the Regularization Parameter.- Section 24. Pseudosolutions.- Section 25. Optimal Regularization.- Section 26. Numerical Algorithms for Regularization Parameters.- Section 27. Heuristic Methods for Choosing a Parameter.- Section 28. The Investigation of Adequacy of Mathematical Models.

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