Iterative Regularization Methods for Nonlinear Ill-Posed Problems - Kaltenbacher, Barbara;Neubauer, Andreas;Scherzer, Otmar
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Nonlinear inverse problems result from 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.
From the contents:
Nonlinear Landweber iteration Modified Landweber methods Newton type methods Multilevel methods Level set methods Applications

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Produktbeschreibung
Nonlinear inverse problems result from 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.

From the contents:

Nonlinear Landweber iteration
Modified Landweber methods
Newton type methods
Multilevel methods
Level set methods
Applications
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Autorenporträt
Barbara Kaltenbacher, University Stuttgart; Andreas Neubauer, Johannes-Kepler-University Linz, Austria; Otmar Scherzer, University Linz, Austria.
Rezensionen
"This well written monograph may become a standard reference on regularization theory for nonlinear inverse problems."
Thorsten Hohage in: Mathematical Reviews 2010c