Barbara Kaltenbacher: Iterative Regularization Methods for Nonlinear Ill-Posed Problems, Gebunden

Beschreibung

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 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.

Klappentext

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
Hansjörg 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