Data-driven identification of latent port-Hamiltonian systems

Conventional physics-based modeling techniques involve high effort, e.g., time and expert knowledge, while data-driven methods often lack interpretability, structure, and sometimes reliability. To mitigate this, we present a data-driven system identification framework that derives models in the port...

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Hauptverfasser:	Rettberg, Johannes, Kneifl, Jonas, Herb, Julius, Buchfink, Patrick, Fehr, Jörg, Haasdonk, Bernard
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Mathematics - Dynamical Systems
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