9783030729851 - Model Reduction of Complex Dynamical Systems: 171 (9 risultati)

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Condizione: New. 2022. Paperback. . . . . .

Taschenbuch. Condizione: Neu. Model Reduction of Complex Dynamical Systems | Peter Benner (u. a.) | Taschenbuch | xii | Englisch | 2022 | Birkhäuser | EAN 9783030729851 | Verantwortliche Person für die EU: Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This contributed volume presents some of the latest research related to model order reduction of complex dynamical systems with a focus on time-dependent problems. Chapters are written by leading researchers and users of model order reduction techniques and are based on presentations given at the 2019 edition of the workshop series Model Reduction of Complex Dynamical Systems - MODRED, held at the University of Graz in Austria. The topics considered can be divided into five categories:system-theoretic methods, such as balanced truncation, Hankel norm approximation, and reduced-basis methods;data-driven methods, including Loewner matrix and pencil-based approaches, dynamic mode decomposition, and kernel-based methods;surrogate modeling for design and optimization, with special emphasis on control and data assimilation;model reduction methods in applications, such as control and network systems, computational electromagnetics, structural mechanics, and fluid dynamics; andmodel order reduction software packages and benchmarks.This volume will be an ideal resource for graduate students and researchers in all areas of model reduction, as well as those working in applied mathematics and theoretical informatics.

Taschenbuch. Condizione: Neu. Neuware -This contributed volume presents some of the latest research related to model order reduction of complex dynamical systems with a focus on time-dependent problems. Chapters are written by leading researchers and users of model order reduction techniques and are based on presentations given at the 2019 edition of the workshop series Model Reduction of Complex Dynamical Systems ¿ MODRED, held at the University of Graz in Austria. The topics considered can be divided into five categories:Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 432 pp. Englisch.

Condizione: New. 2022. Paperback. . . . . . Books ship from the US and Ireland.

Condizione: new. Questo è un articolo print on demand.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This contributed volume presents some of the latest research related to model order reduction of complex dynamical systems with a focus on time-dependent problems. Chapters are written by leading researchers and users of model order reduction techniques and are based on presentations given at the 2019 edition of the workshop series Model Reduction of Complex Dynamical Systems - MODRED, held at the University of Graz in Austria. The topics considered can be divided into five categories:system-theoretic methods, such as balanced truncation, Hankel norm approximation, and reduced-basis methods;data-driven methods, including Loewner matrix and pencil-based approaches, dynamic mode decomposition, and kernel-based methods;surrogate modeling for design and optimization, with special emphasis on control and data assimilation;model reduction methods in applications, such as control and network systems, computational electromagnetics, structural mechanics, and fluid dynamics; andmodel order reduction software packages and benchmarks.This volume will be an ideal resource for graduate students and researchers in all areas of model reduction, as well as those working in applied mathematics and theoretical informatics. 432 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the latest research on model order reduction of complex dynamical systemsFeatures contributions from leading researchers and users of model order reduction techniquesOffers an ideal resource for graduate students and researchers in.