Regularization Methods in Banach Spaces
De Gruyter (Publisher)
Published on 30. July 2012
Book
Mixed media product
XI, 283 pages
978-3-11-220450-4 (ISBN)
Article is exhausted; no reprint
Description
Regularization methods aimed at finding stable approximate solutions are a necessary tool to tackle inverse and ill-posed problems. Usually the mathematical model of an inverse problem consists of an operator equation of the first kind and often the associated forward operator acts between Hilbert spaces. However, for numerous problems the reasons for using a Hilbert space setting seem to be based rather on conventions than on an approprimate and realistic model choice, so often a Banach space setting would be closer to reality. Furthermore, sparsity constraints using general Lp-norms or the BV-norm have recently become very popular. Meanwhile the most well-known methods have been investigated for linear and nonlinear operator equations in Banach spaces. Motivated by these facts the authors aim at collecting and publishing these results in a monograph.
More details
Series
Language
English
Place of publication
Berlin
Germany
Target group
Professional and scholarly
US School Grade: College Graduate Student
Illustrations
Includes a print version and an ebook
Dimensions
Height: 24 cm
Width: 17 cm
ISBN-13
978-3-11-220450-4 (9783112204504)
Schweitzer Classification
Persons
Thomas Schuster, Carl von Ossietzky Universität Oldenburg, Germany;Barbara Kaltenbacher, University of Stuttgart, Germany; Bernd Hofmann, Chemnitz University of Technology, Germany; Kamil S. Kazimierski, University of Bremen, Germany.