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Model Order Reduction: Volume 1: Methods PDF

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About Model Order Reduction: Volume 1: Methods

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.

Detailed Information

Author:Peter Benner
ISBN:9783110500431
File Size:12
Format:PDF
Price:FREE
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