Bayesian State and Parameter Estimation of Uncertain Dynamical Systems
By Jianye Ching, James L. Beck, K. Porter. 2006
245 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/5398649e8515a8281fd3928416840ed180727cfa
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Costas Papadimitriou
- Eleni N. Chatzi
- Savvas P. Triantafyllou
- Geert Lombaert
- Fayçal Ikhouane
- M. Chatzis
- José Rodellar
- Saeed Eftekhar Azam
In Statistical and Nonlinear Physics
Citations in the corpus
- A Discontinuous Extended Kalman Filter for non-smooth dynamic problems (2017, background): “, 470 the fact that the EKF ([31, 32]) may encounter difficulties in determining the values of parameters β and γ (or ∆1 and ∆2).”
- Design of sensor networks for instantaneous inversion of modally reduced order models in structural dynamics (2015, background): “Several state estimation algorithms have been proposed for linear as well as for non-linear systems [8, 9, 10, 11].”
- Systems with Hysteresis: Analysis, Identification and Control Using the Bouc-Wen Model (2007, methodology): “Bayesian parameter estimation is used in References [35] to [38].”
- A dual Kalman filter approach for state estimation via output-only acceleration measurements (2015, methodology): “[16] compared the performance of the EKF with that of the particle filter (PF) applied to identification of system matrices of a linear multi storey shear building.”