Iterative Regularization Methods for Nonlinear Ill-posed Problems.

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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 a...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Kaltenbacher, Barbara
Otros Autores: Neubauer, Andreas, Scherzer, Otmar
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin : Walter de Gruyter, 2008.
Colección:Radon Series on Computational and Applied Mathematics, v. 6.
Temas:
Differential equations, Partial > Improperly posed problems.
Iterative methods (Mathematics)
Équations aux dérivées partielles > Problèmes mal posés.
Itération (Mathématiques)
MATHEMATICS / Mathematical Analysis.
Differential equations, Partial > Improperly posed problems
Acceso en línea:Texto completo
Descripción
Sumario: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.
Descripción Física:1 online resource (204 pages)
ISBN:9783110208276
311020827X

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