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Iterative Regularization Methods for Nonlinear Ill-Posed Problems : Radon Series on Computational and Applied Mathematics - Andreas Neubauer

Iterative Regularization Methods for Nonlinear Ill-Posed Problems

By: Andreas Neubauer, Otmar Scherzer, Barbara Kaltenbacher

Hardcover | 20 May 2008

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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.

The series is devoted to the publication of high-level monographs, surveys and proceedings which cover the whole spectrum of computational and applied mathematics.

The books of this series are addressed to both specialists and advanced students.

Interested authors may submit book proposals to the Managing Editor or to any member of the Editorial Board.

Managing Editor
Otmar Scherzer, RICAM, Linz, Austria; University of Vienna, Austria

Editorial Board
Hansjorg Albrecher, University of Lausanne, Switzerland
Ronald H. W. Hoppe, University of Houston, USA
Karl Kunisch, RICAM, Linz, Austria; University of Graz, Austria
Harald Niederreiter, RICAM, Linz, Austria
Christian Schmeiser, University of Vienna, Austria

Industry Reviews

"This well written monograph may become a standard reference on regularization theory for nonlinear inverse problems."
Thorsten Hohage in: Mathematical Reviews 2010c

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