Data driven discovery of cyber physical systems

Discovery of hybrid dynamical models for real-world cyber-physical systems remains a challenge. This paper proposes a general framework for automating mechanistic modeling of hybrid dynamical systems from observed data with low computational complexity and noise resilience.

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Auteurs principaux: Ye Yuan, Xiuchuan Tang, Wei Zhou, Wei Pan, Xiuting Li, Hai-Tao Zhang, Han Ding, Jorge Goncalves
Format: article
Langue:EN
Publié: Nature Portfolio 2019
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Accès en ligne:https://doaj.org/article/c7daebc20a2d4e6b8ab01d1077cfe84d
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