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Physics-aware tuning of the unscented Kalman filter: statistical framework for solving inverse problems involving nonlinear dynamical systems and missing data

Esmaeil Ghorbani, Quentin Dollon and Frédérick P. Gosselin

Article (2024)

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Department: Department of Mechanical Engineering
Research Center: LM2 - Laboratory for Multi-scale Mechanics
PolyPublie URL: https://publications.polymtl.ca/58641/
Journal Title: Nonlinear Dynamics
Publisher: Springer Nature
DOI: 10.1007/s11071-024-09760-z
Official URL: https://doi.org/10.1007/s11071-024-09760-z
Date Deposited: 26 Jun 2024 12:51
Last Modified: 25 Sep 2024 16:51
Cite in APA 7: Ghorbani, E., Dollon, Q., & Gosselin, F. P. (2024). Physics-aware tuning of the unscented Kalman filter: statistical framework for solving inverse problems involving nonlinear dynamical systems and missing data. Nonlinear Dynamics, 23 pages. https://doi.org/10.1007/s11071-024-09760-z

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