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 Frederick 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:	08 Apr 2025 07:28

Cite in APA 7:	Ghorbani, E., Dollon, Q., & Gosselin, F. (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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