Model Order Reduction

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 second volume focuses on app...

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Bibliographische Detailangaben
Format: Online
Sprache:Englisch
Veröffentlicht: De Gruyter 2021
Schlagworte:
Online-Zugang:ONIX_20210211_9783110671490_65
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Beschreibung
Zusammenfassung: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 second volume focuses on applications in engineering, biomedical engineering, computational physics and computer science.