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Iterative Regularization Methods for Nonlinear Ill-Posed Problems, PDF eBook

Iterative Regularization Methods for Nonlinear Ill-Posed Problems PDF

Part of the Radon Series on Computational and Applied Mathematics series

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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 are based on iteration methods, e.g., nonlinear Landweber iteration, level set methods, multilevel methods and Newton type methods.

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