Data-driven discovery of linear dynamical systems from noisy data
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Engineering,General Materials Science
Link
https://link.springer.com/content/pdf/10.1007/s11431-023-2520-6.pdf
Reference42 articles.
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4. Wang Y, Fang H, Jin J, et al. Data-driven discovery of stochastic differential equations. Engineering, 2022, 17: 244–252
5. Shen T, Dong Y L, He D X, et al. Online identification of time-varying dynamical systems for industrial robots based on sparse Bayesian learning. Sci China Tech Sci, 2022, 65: 386–395
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