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

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Model Order Reduction : System- and Data-driven Methods and Algorithms

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