Druck auf Anfrage Neuware - Printed after ordering - An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This first volume focuses on real-time control theory, data assimilation, real-time visualization, high-dimensional state spaces and interaction of different reduction techniques.

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Bibliographic Details

Title: Model Order Reduction, Volume 1, System- and Data-Driven Methods and Algorithms
Publisher: De Gruyter, De Gruyter
Publication Date: 2021
Language: English
ISBN 10: 3110500434
ISBN 13: 9783110500431
Binding: Buch
Condition: Neu
Dimensions: 246 millimeters width by 175 millimeters height by 30 millimeters depth
Weight: 913 grams

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Synopsis

An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This first volume focuses on real-time control theory, data assimilation, real-time visualization, high-dimensional state spaces and interaction of different reduction techniques.

About the Author

Benner, MPI, GE; Grivet-T., POLITO, Quarteroni, Politec., Rozza, SISSA, IT; Schilders, TU Eind., NE; Silveira, INESC-ID, PT

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