Editors:
- First book relating the inversion theory and recent developments with real applications
- Combines optimization and regularization for solving inverse problems
- Covers frontiers on multi-disciplinary subjects areas
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Table of contents (14 chapters)
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Front Matter
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Introduction
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Front Matter
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Regularization Theory and Recent Developments
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Front Matter
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Nonstandard Regularization and Advanced Optimization Theory and Methods
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Front Matter
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Numerical Inversion in Geoscience and Quantitative Remote Sensing
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Front Matter
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Back Matter
About this book
Editors and Affiliations
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Key Laboratory of Petroleum Geophysics Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China
Yanfei Wang, Changchun Yang
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Department of Mathematics Faculty of Physics, Lomonosov Moscow State University, Moscow, Russia
Anatoly G. Yagola
Bibliographic Information
Book Title: Optimization and Regularization for Computational Inverse Problems and Applications
Editors: Yanfei Wang, Changchun Yang, Anatoly G. Yagola
DOI: https://doi.org/10.1007/978-3-642-13742-6
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2011
Hardcover ISBN: 978-3-642-13741-9Published: 04 January 2011
eBook ISBN: 978-3-642-13742-6Published: 29 June 2011
Edition Number: 1
Number of Pages: 400
Number of Illustrations: 36 b/w illustrations
Additional Information: Jointly published with Higher Education Press.
Topics: Computational Mathematics and Numerical Analysis, Mathematical and Computational Engineering, Remote Sensing/Photogrammetry