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Model reduction and approximation : theory and algorithms

Author: Peter Benner; Albert Cohen; Mario Ohlberger; Karen Willcox; Society for Industrial and Applied Mathematics,
Publisher: Philadelphia, Pennsylvania : Society for Industrial and Applied Mathematics, [2017]
Series: SIAM e-books.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Many physical, chemical, biomedical, and technical processes can be described by partial differential equations or dynamical systems. 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 remains a central research challenge. This book presents a tutorial introduction to recent  Read more...
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Genre/Form: Livres numériques
Additional Physical Format: Version imprimée:
(DLC) 2017012782
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Peter Benner; Albert Cohen; Mario Ohlberger; Karen Willcox; Society for Industrial and Applied Mathematics,
ISBN: 9781611974829 1611974828
OCLC Number: 1041874753
Notes: Versement en lot.
In SIAM e-books.
Description: 1 ressource en ligne (xii, 412 pages).
Contents: Preface --
part I. Sampling-based methods --
1. Pod for linear-quadratic optimal control --
2. A tutorial on RB-methods --
3. The theoretical foundation of reduced basis methods --
part II. Tensor-based methods --
4. Low-rank methods for high-dimensional approximation --
5. Model reduction for high-dimensional parametric problems by tensor techniques --
part III. System-theoretic methods --
6. Model order reduction based on systems building --
7. Interpolatory model reduction --
8. The loewner framework for model reduction --
9. Comparison of methods for PMOR.
Series Title: SIAM e-books.
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.

Abstract:

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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