Iterative Regularization Methods for Nonlinear Ill-Posed Problems [E-Book].
Scherzer, Otmar
Kaltenbacher, Barbara / Neubauer, Andreas
Berlin : De Gruyter
1 online resource (VIII, 194 S.)
englisch
9783110204209
9783110208276
Radon Series on Computational and Applied Mathematics ; 6
Full Text
Biographical note: Barbara Kaltenbacher, Universität Stuttgart; Andreas Neubauer, Johannes-Kepler-Universität Linz, Österreich; Otmar Scherzer, Universität Linz, Österreich.
Biographical note: Barbara Kaltenbacher, University Stuttgart; Andreas Neubauer, Johannes-Kepler-University Linz, Austria; Otmar Scherzer, University Linz, Austria.
Main description: 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.
Main description: 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
Review text: "This well written monograph may become a standard reference on regularization theory for nonlinear inverse problems."Thorsten Hohage in: Mathematical Reviews 2010c