Reduced Order Methods for Modeling and Computational Reduction

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Éditeur :

Springer


Collection :

MS&A

Paru le : 2014-06-05

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Description
This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics.

Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects.
This book is primarily addressed to computational scientists interested in computational reduction techniques for large scale differential problems.
Pages
334 pages
Collection
MS&A
Parution
2014-06-05
Marque
Springer
EAN papier
9783319020891
EAN EPUB
9783319020907

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
33
Taille du fichier
10783 Ko
Prix
94,94 €