Editors:
- International group of expert editors and contributors.
- Presents all new material in the areas of projection and fixed point algorithms for mathematics and the applied sciences.
- Basis for innovative research from a broad range of topics such as variational analysis, numerical linear algebra, biotechnology, materials science, computational solid state physics, and chemistry.
- Areas of application include engineering (image and signal reconstruction and decompression problems), computer tomography and radiation treatment planning (convex feasibility problems), astronomy (adaptive optics), crystallography (molecular structure reconstruction), computational chemistry (molecular structure simulation).
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 49)
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Table of contents (18 chapters)
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Front Matter
About this book
"Fixed-Point Algorithms for Inverse Problems in Science and Engineering" presents some of the most recent work from top-notch researchers studying projection and other first-order fixed-point algorithms in several areas of mathematics and the applied sciences. The material presented provides a survey of the state-of-the-art theory and practice in fixed-point algorithms, identifying emerging problems driven by applications, and discussing new approaches for solving these problems.
This book incorporates diverse perspectives from broad-ranging areas of research including, variational analysis, numerical linear algebra, biotechnology, materials science, computational solid-state physics, and chemistry.
Topics presented include:
Theory of Fixed-point algorithms: convex analysis, convex optimization, subdifferential calculus, nonsmooth analysis, proximal point methods, projection methods, resolvent and related fixed-point theoretic methods, and monotone operator theory.
Numerical analysis of fixed-point algorithms: choice of step lengths, of weights, of blocks for block-iterative and parallel methods, and of relaxation parameters; regularization of ill-posed problems; numerical comparison of various methods.
Areas of Applications: engineering (image and signal reconstruction and decompression problems), computer tomography and radiation treatment planning (convex feasibility problems), astronomy (adaptive optics), crystallography (molecular structure reconstruction), computational chemistry (molecular structure simulation) and other areas.
Because of the variety of applications presented, this book can easily serve as a basis for new and innovated research and collaboration.
Editors and Affiliations
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Okanagan Campus, Department of Mathematics and Statistic, University of British Columbia, Kelowna, Canada
Heinz H. Bauschke
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School of Mathematics & Statistics, Division of Information Technology, University of South Australia, Mawson Lakes, Australia
Regina S. Burachik
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Laboratoire Jacques-Louis Lions, Université Pierre et Marie Curie, Paris, France
Patrick L. Combettes
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Dept. Physics, Lab. Atomic & Solid State, Cornell University, Ithaca, USA
Veit Elser
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Institut für Numerische und Angewandte M, Universität Göttingen, Göttingen, Germany
D. Russell Luke
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Faculty of Mathematics, Dept. Combinatorics & Optimization, University of Waterloo, Waterloo, Canada
Henry Wolkowicz
Bibliographic Information
Book Title: Fixed-Point Algorithms for Inverse Problems in Science and Engineering
Editors: Heinz H. Bauschke, Regina S. Burachik, Patrick L. Combettes, Veit Elser, D. Russell Luke, Henry Wolkowicz
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-1-4419-9569-8
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC 2011
Hardcover ISBN: 978-1-4419-9568-1
Softcover ISBN: 978-1-4614-2900-5
eBook ISBN: 978-1-4419-9569-8
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 1
Number of Pages: XII, 404
Topics: Computational Mathematics and Numerical Analysis, Calculus of Variations and Optimal Control; Optimization, Mathematical Modeling and Industrial Mathematics, Algorithm Analysis and Problem Complexity, Theoretical, Mathematical and Computational Physics