Description
| Summary: | 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.
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| Physical Description: | 1 online resource (xi, 283 pages) : illustrations |
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| Bibliography: | Includes bibliographical references (pages 265-279) and index. |
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| ISBN: | 9783110255720
3110255723
9783112204504
3112204506
1283627922
9781283627924
9786613940377
6613940372 |
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| ISSN: | 1865-3707 ; |
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| Language: | English. |
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| Source of Description, Etc. Note: | Print version record. |
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