Regularization Methods in Banach Spaces - Couverture rigide

Livre 9 sur 28: Radon Series on Computational and Applied Mathematics

Schuster, Thomas ; Kaltenbacher, Barbara ; Hofmann, Bernd ; Kazimierski, Kamil S.

9783110255249: Regularization Methods in Banach Spaces

Couverture rigide

ISBN 10 : 3110255243 ISBN 13 : 9783110255249

Editeur : De Gruyter, 2012

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Regularization methods aimed at finding stable approximate solutions are a necessary tool to tackle inverse and ill-posed problems. Usually the mathematical model of an inverse problem consists of an operator equation of the first kind and often the

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� propos de l?auteur

Thomas Schuster, Carl von Ossietzky Universit�t Oldenburg, Germany; Barbara Kaltenbacher, University of Stuttgart, Germany; Bernd Hofmann, Chemnitz University of Technology, Germany; Kamil S. Kazimierski, University of Bremen, Germany.

Les informations fournies dans la section � A propos du livre � peuvent faire r�f�rence � une autre �dition de ce titre.

�diteur: De Gruyter
Date d'�dition: 2012
Langue: anglais
ISBN 10: 3110255243
ISBN 13: 9783110255249
Reliure: Reli�
Nombre de pages: 294
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productsafety@degruyterbrill.com

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Regularization Methods in Banach Spaces

Thomas Schuster

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Regularization Methods in Banach Spaces

Thomas Schuster|Barbara Kaltenbacher|Bernd Hofmann|Kamil S. Kazimierski

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Regularization Methods in Banach Spaces (eng)

Schuster, Thomas

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ISBN 10 : 3110255243 ISBN 13 : 9783110255249

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Regularization Methods in Banach Spaces

Thomas Schuster

Edit� par De Gruyter, De Gruyter Jul 2012, 2012

ISBN 10 : 3110255243 ISBN 13 : 9783110255249

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Regularization methods aimed at finding stable approximate solutions are a necessary tool to tackle inverse and ill-posed problems. Inverse problems arise in a large variety of applications ranging from medical imaging and non-destructive testing via finance to systems biology. Many of these problems belong to the class of parameter identification problems in partial differential equations (PDEs) and thus are computationally demanding and mathematically challenging. Hence there is a substantial need for stable and efficient solvers for this kind of problems as well as for a rigorous convergence analysis of these methods. This monograph consists of five parts. Part I motivates the importance of developing and analyzing regularization methods in Banach spaces by presenting four applications which intrinsically demand for a Banach space setting and giving a brief glimpse of sparsity constraints. Part II summarizes all mathematical tools that are necessary to carry out an analysis in Banach spaces. Part III represents the current state-of-the-art concerning Tikhonov regularization in Banach spaces. Part IV about iterative regularization methods is concerned with linear operator equations and the iterative solution of nonlinear operator equations by gradient type methods and the iteratively regularized Gau�-Newton method. Part V finally outlines the method of approximate inverse which is based on the efficient evaluation of the measured data with reconstruction kernels. 296 pp. Englisch. N� de r�f. du vendeur 9783110255249

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Regularization Methods in Banach Spaces

Thomas Schuster (u. a.)

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Regularization Methods in Banach Spaces

Kazimierski Kamil S. Hofmann Bernd Kaltenbacher Barbara Schuster Thomas

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Regularization Methods in Banach Spaces

Thomas Schuster

Edit� par De Gruyter, De Gruyter, 2012

ISBN 10 : 3110255243 ISBN 13 : 9783110255249

Neuf Couverture rigide

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Regularization methods aimed at finding stable approximate solutions are a necessary tool to tackle inverse and ill-posed problems. Inverse problems arise in a large variety of applications ranging from medical imaging and non-destructive testing via finance to systems biology. Many of these problems belong to the class of parameter identification problems in partial differential equations (PDEs) and thus are computationally demanding and mathematically challenging. Hence there is a substantial need for stable and efficient solvers for this kind of problems as well as for a rigorous convergence analysis of these methods. This monograph consists of five parts. Part I motivates the importance of developing and analyzing regularization methods in Banach spaces by presenting four applications which intrinsically demand for a Banach space setting and giving a brief glimpse of sparsity constraints. Part II summarizes all mathematical tools that are necessary to carry out an analysis in Banach spaces. Part III represents the current state-of-the-art concerning Tikhonov regularization in Banach spaces. Part IV about iterative regularization methods is concerned with linear operator equations and the iterative solution of nonlinear operator equations by gradient type methods and the iteratively regularized Gau�-Newton method. Part V finally outlines the method of approximate inverse which is based on the efficient evaluation of the measured data with reconstruction kernels. N� de r�f. du vendeur 9783110255249

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Regularization Methods in Banach Spaces

Schuster, Thomas/ Kaltenbacher, Barbara/ Hofmann, Bernd/ Kazimierski, Kamil S.

Edit� par De Gruyter, 2012

ISBN 10 : 3110255243 ISBN 13 : 9783110255249

Neuf Couverture rigide

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Hardcover. Etat : Brand New. 283 pages. 9.50x6.75x0.75 inches. In Stock. N� de r�f. du vendeur __3110255243

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Regularization Methods in Banach Spaces

Kamil S. Kazimierski Bernd Hofmann Barbara Kaltenbacher Thomas Schuster

Edit� par Walter de Gruyter, Incorporated, 2012

ISBN 10 : 3110255243 ISBN 13 : 9783110255249

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Regularization Methods in Banach Spaces

Kaltenbacher, Barbara

Edit� par De Gruyter, 2012

ISBN 10 : 3110255243 ISBN 13 : 9783110255249

Ancien ou d'occasion Couverture rigide

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Etat : Sehr gut. Zustand: Sehr gut | Seiten: 296 | Sprache: Englisch | Produktart: B�cher | Regularization methods aimed at finding stable approximate solutions are a necessary tool to tackle inverse and ill-posed problems. Inverse problems arise in a large variety of applications ranging from medical imaging and non-destructive testing via finance to systems biology. Many of these problems belong to the class of parameter identification problems in partial differential equations (PDEs) and thus are computationally demanding and mathematically challenging. Hence there is a substantial need for stable and efficient solvers for this kind of problems as well as for a rigorous convergence analysis of these methods. This monograph consists of five parts. Part I motivates the importance of developing and analyzing regularization methods in Banach spaces by presenting four applications which intrinsically demand for a Banach space setting and giving a brief glimpse of sparsity constraints. Part II summarizes all mathematical tools that are necessary to carry out an analysis in Banach spaces. Part III represents the current state-of-the-art concerning Tikhonov regularization in Banach spaces. Part IV about iterative regularization methods is concerned with linear operator equations and the iterative solution of nonlinear operator equations by gradient type methods and the iteratively regularized Gau�-Newton method. Part V finally outlines the method of approximate inverse which is based on the efficient evaluation of the measured data with reconstruction kernels. N� de r�f. du vendeur 12328034/12

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