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Iterative Regularization Methods for Nonlinear Ill-Posed Problems von Kaltenbacher, Barbara (eBook)

  • Erscheinungsdatum: 25.09.2008
  • Verlag: De Gruyter
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Iterative Regularization Methods for Nonlinear Ill-Posed Problems

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.


Barbara Kaltenbacher , University Stuttgart; Andreas Neubauer , Johannes-Kepler-University Linz, Austria; Otmar Scherzer , University Linz, Austria.

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