[[Category:data-driven]]
...ay to fasten the gust simulation step and simplify the analysis by mean of data-driven model approximation in the Loewner framework is proposed, as well as a desc
5 KB (701 words) - 06:30, 17 June 2025
...yDMD] is a Python package that uses Dynamic Mode Decomposition (DMD) for a data-driven model simplification based on spatiotemporal coherent structures. DMD is a
...inks">[https://doi.org/10.1137/1.9781611974508 Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems]</span>", Vol. 149, SIAM, 2016</ref>
3 KB (467 words) - 18:00, 11 February 2019
[[Category:data-driven]]
...las, "<span class="plainlinks">[https://doi.org/10.1016/bs.hna.2021.12.015 Data-driven modeling and control of large-scale dynamical systems in the Loewner framew
8 KB (1,228 words) - 10:49, 12 October 2022
.... C. Antoulas, <span class="plainlinks">[https://doi.org/10.1137/130914619 Data-Driven Parametrized Model Reduction in the Loewner Framework]</span>, SIAM J. Sci.
5 KB (621 words) - 10:38, 30 November 2023
...2 Balancing-related model reduction methods]</span>". Volume 1 System- and Data-Driven Methods and Algorithms: 15--56, 2021.</ref>
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* Data-driven model order reduction with Dynamic Mode Decomposition, Loewner matrices, Ei
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It is a data-driven method that directly constructs a ROM using only measured data (samples of
...A.C. Antoulas. <span class="plainlinks">[https://doi.org/10.1002/nla.2200 Data-driven model order reduction of quadratic-bilinear systems]</span>. Numercial Line
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