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Model reduction and approximation theory and algorithms

Author: Peter Benner; Albert Cohen; Mario Ohlberger; Karen Willcox
Publisher: Philadelphia Society for Industrial and Applied Mathematics [2017]
Series: Computational science and engineering, 15.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:

In spite of increasing computational capacities, many problems are of such high complexity that they are solvable only with severe simplifications, and the design of efficient numerical schemes  Read more...

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Additional Physical Format: Erscheint auch als:
Model reduction and approximation
Philadelphia : SIAM, Society for Industrial and Applied Mathematics, [2017], 2017
1 Online-Ressource
Online-Ausgabe
Document Type: Book
All Authors / Contributors: Peter Benner; Albert Cohen; Mario Ohlberger; Karen Willcox
ISBN: 9781611974812 161197481X 9781611974829 1611974828
OCLC Number: 993615812
Description: Seiten cm
Contents: PrefacePart I: Sampling-Based MethodsChapter 1: POD for Linear-Quadratic Optimal ControlChapter 2: A Tutorial on RB-MethodsChapter 3: The Theoretical Foundation of Reduced Basis MethodsPart II: Tensor-Based MethodsChapter 4: Low-Rank Methods for High-Dimensional ApproximationChapter 5: Model Reduction for High-Dimensional Parametric Problems by Tensor TechniquesPart III: System-Theoretic MethodsChapter 6: Model Order Reduction Based on Systems BuildingChapter 7: Interpolatory Model ReductionChapter 8: The Loewner Framework for Model ReductionChapter 9: Comparison of Methods for PMORIndex.
Series Title: Computational science and engineering, 15.
Responsibility: edited by Peter Benner, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany, Albert Cohen, Université Pierre at Marie Curie, Paris, France, Mario Ohlberger, Universität Münster, Münster, Germany, Karen Willcox, Massachusetts Institute of Technology, Cambridge, Massachusetts

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