Methods for Solving Incorrectly Posed Problems

V. A. Morozov

ISBN 10: 0387960597 / ISBN 13: 9780387960593

Editore: Springer New York, Springer US Nov 1984, 1984

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This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 280 pp. Englisch.

Codice articolo 9780387960593

Dati bibliografici

• Titolo: Methods for Solving Incorrectly Posed Problems
• Editore: Springer New York, Springer US Nov 1984
• Data di pubblicazione: 1984
• Lingua: Inglese
• ISBN 10: 0387960597
• ISBN 13: 9780387960593
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 16 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 16 millimetri di profondità
• Peso: 429 grammi

Descrizione articolo

Riassunto

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.

Contenuti

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.