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Regularization of Ill-Posed Problems by Iteration Methods

This volume presents new results in regularization of ill-posed problems by iteration methods, which is one of the most important and rapidly developing topics of the theory of ill-posed problems. The new theoretical results are connected with the proposed united approach to the proof of regularizing properties of the `classical' iteration methods (steepest descent, conjugate direction) complemented by the stopping rule depending on the level of errors in the input data. Much emphasis is given to the choice of the iteration index as the regularization parameter and to the rate convergence estimates of the approximate solutions. Results of calculations for important applications in non-linear thermophysics are also presented. Audience: This work will be a useful resource for specialists in the theory of partial differential and integral equations, in numerical analysis and in theory and methods.

Gedetalleerde informatie over het boek. - Regularization of Ill-Posed Problems by Iteration Methods


EAN (ISBN-13): 9789048153824
ISBN (ISBN-10): 9048153824
pocket book
Verschijningsjaar: 2010
Uitgever: Springer-Verlag GmbH
356 Bladzijden
Gewicht: 0,538 kg
Taal: eng/Englisch

Boek bevindt zich in het datenbestand sinds 2012-05-19T15:14:40+02:00 (Amsterdam)
Detailpagina laatst gewijzigd op 2016-04-01T23:24:13+02:00 (Amsterdam)
ISBN/EAN: 9789048153824

ISBN - alternatieve schrijfwijzen:
90-481-5382-4, 978-90-481-5382-4


Gegevens van de uitgever

Auteur: S.F. Gilyazov; N.L. Gol'dman
Titel: Mathematics and Its Applications; Regularization of Ill-Posed Problems by Iteration Methods
Uitgeverij: Springer; Springer Netherland
342 Bladzijden
Verschijningsjaar: 2010-12-09
Dordrecht; NL
Gedrukt / Gemaakt in
Gewicht: 0,540 kg
Taal: Engels
106,99 € (DE)
109,99 € (AT)
133,63 CHF (CH)
POD
IX, 342 p.

BC; Previously published in hardcover; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Numerische Mathematik; Verstehen; Calc; Calculation; DEX; Integral equation; Volume; algorithms; convergence; equation; integral; iteration; numerical analysis; online; operator; proof; partial differential equations; B; Computational Mathematics and Numerical Analysis; Operator Theory; Partial Differential Equations; Integral Equations; Automotive Engineering; Computational Mathematics and Numerical Analysis; Operator Theory; Differential Equations; Integral Equations; Automotive Engineering; Mathematics and Statistics; Funktionalanalysis und Abwandlungen; Differentialrechnung und -gleichungen; Integralrechnung und -gleichungen; Fahrzeugbau; BB

Preface. Introduction. 1. Regularizing Algorithms for Linear Ill-Posed Problems: Unified Approach. 2. Iteration Steepest Descent Methods for Linear Operator Equations. 3. Iteration Conjugate Direction Methods For Linear Operator Equations. 4. Iteration Steepest Descent Methods for Nonlinear Operator Equations. 5. Iteration Methods for Ill-Posed Constrained Minimization Problems. 6. Descriptive Regularization Algorithms on the Basis of the Conjugate Gradient Projection Method. Bibliography. Index.

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9789401594820 Regularization of Ill-Posed Problems by Iteration Methods (S.F. Gilyazov; N.L. Gol'dman)


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