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Abstract
We aim at improving extended dynamic mode decomposition that allows to linearize nonlinear systems.
Indeed, the EDMD algorithm provides a finite-dimensional representation of the Koopman operator.
Finally, the reservoir computer is trained to produce an efficient dictionary
Indeed, the EDMD algorithm provides a finite-dimensional representation of the Koopman operator.
Finally, the reservoir computer is trained to produce an efficient dictionary
Original language | English |
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Title of host publication | Book of Abstracts |
Subtitle of host publication | 38th Benelux Meeting on Systems and Control |
Editors | Panos Patrinos, Ivan Markovsky, Wim Michiels, Jan Swevers, Steffen Waldherr |
Publisher | KU Leuven |
Pages | 42 |
Number of pages | 211 |
ISBN (Print) | 9789082825954 |
Publication status | Published - 19 Mar 2019 |
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Dive into the research topics of 'Dictionary learning in Extended Dynamic Mode Decomposition using a reservoir computer'. Together they form a unique fingerprint.Activities
- 1 Participation in conference
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38th Benelux Meeting on Systems and Control
Marvyn Gulina (Contributor)
19 Mar 2019 → 22 Mar 2019Activity: Participating in or organising an event types › Participation in conference