Iterative Regularization Methods for Nonlinear Ill-Posed Problems (Radon Series on Computational and Applied Mathematics, 6) - Hardcover
Synopsis
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.
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About the Authors
Barbara Kaltenbacher, Universität Stuttgart; Andreas Neubauer, Johannes-Kepler-Universität Linz, Österreich; Otmar Scherzer, Universität Linz, Österreich.
Barbara Kaltenbacher, University Stuttgart; Andreas Neubauer, Johannes-Kepler-University Linz, Austria; Otmar Scherzer, University Linz, Austria.
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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.; 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 iterationModified Landweber methodsNewton type methodsMultilevel methodsLevel set methodsApplications 204 pp. Englisch. Seller Inventory # 9783110204209
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