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Model Reduction of Parametrized Systems

  • Peter Benner
  • Mario Ohlberger
  • Anthony Patera
  • Gianluigi Rozza
  • Karsten Urban

Part of the MS&A book series (MS&A, volume 17)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Silke Glas, Antonia Mayerhofer, Karsten Urban
    Pages 1-16
  3. Thomas Horger, Barbara Wohlmuth, Linus Wunderlich
    Pages 91-106
  4. Robert O’Connor, Martin Grepl
    Pages 121-136
  5. Andreas Buhr, Christian Engwer, Mario Ohlberger, Stephan Rave
    Pages 137-148
  6. Francesco Ballarin, Gianluigi Rozza, Yvon Maday
    Pages 149-167
  7. Mario Ohlberger, Stephan Rave, Felix Schindler
    Pages 169-182
  8. Andrea Manzoni, Federico Negri
    Pages 183-199
  9. Martin Gubisch, Ira Neitzel, Stefan Volkwein
    Pages 213-234
  10. Davide Baroli, Cristina Maria Cova, Simona Perotto, Lorenzo Sala, Alessandro Veneziani
    Pages 235-254
  11. Thomas Franz, Ralf Zimmermann, Stefan Görtz
    Pages 255-269
  12. Christian Himpe, Mario Ohlberger
    Pages 271-283
  13. Peter Benner, Pawan Goyal, Martin Redmann
    Pages 285-300
  14. J. Nathan Kutz, Syuzanna Sargsyan, Steven L. Brunton
    Pages 301-315
  15. Alessandro Alla, Giulia Fabrini, Maurizio Falcone
    Pages 317-331
  16. Alessandro Alla, Andreas Schmidt, Bernard Haasdonk
    Pages 333-347
  17. Alessandro Castagnotto, Christopher Beattie, Serkan Gugercin
    Pages 349-365
  18. Murat Uzunca, Bülent Karasözen
    Pages 403-419
  19. Lorenzo Codecasa, Konstantin Weise, Luca Di Rienzo, Jens Haueisen
    Pages 421-437
  20. Walid Kheriji, Yalchin Efendiev, Victor Manuel Calo, Eduardo Gildin
    Pages 471-490
  21. Michael Baumann, Dominik Hamann, Peter Eberhard
    Pages 491-504

About this book

Introduction

The special volume offers a global guide to new concepts and approaches concerning the following topics: reduced basis methods, proper orthogonal decomposition, proper generalized decomposition, approximation theory related to model reduction, learning theory and compressed sensing, stochastic and high-dimensional problems, system-theoretic methods, nonlinear model reduction, reduction of coupled problems/multiphysics, optimization and optimal control, state estimation and control, reduced order models and domain decomposition methods, Krylov-subspace and interpolatory methods, and applications to real industrial and complex problems.

The book represents the state of the art in the development of reduced order methods. It contains contributions from internationally respected experts, guaranteeing a wide range of expertise and topics. Further, it reflects an important effor

t, carried out over the last 12 years, to build a growing research community in this field.

Though not a textbook, some of the chapters can be used as reference materials or lecture notes for classes and tutorials (doctoral schools, master classes).

Keywords

Model order reduction Reduced order methods Reduced order modeling Offline-Online computing Parametrized systems held by PDEs

Editors and affiliations

  • Peter Benner
    • 1
  • Mario Ohlberger
    • 2
  • Anthony Patera
    • 3
  • Gianluigi Rozza
    • 4
  • Karsten Urban
    • 5
  1. 1.Computational Methods in Systems and Control TheoryMax Planck Institute for Dynamics of Complex Technical SystemsMagdeburgGermany
  2. 2.Institute for Computational and Applied MathematicsUniversity of Münster MünsterGermany
  3. 3.Massachusetts Institute of TechnologyMIT CambridgeUSA
  4. 4.SISSA MathLabInternational School for Adv. Studies TriesteItaly
  5. 5.Institute of Numerical MathematicsUlm University UlmGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-58786-8
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-58785-1
  • Online ISBN 978-3-319-58786-8
  • Series Print ISSN 2037-5255
  • Series Online ISSN 2037-5263
  • Buy this book on publisher's site
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