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Model Order Reduction.

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Abstract

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.


Book
Model Order Reduction.
Authors: --- --- --- --- --- et al.
ISBN: 3110499002 3110497751 3110500442 Year: 2020 Publisher: Berlin/Boston De Gruyter

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Abstract

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 three-volume handbook covers methods as well as applications. This third volume focuses on applications in engineering, biomedical engineering, computational physics and computer science.

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