Showing eess.SYShow all
3 papers · 1 filter
eess.SY2026
Natural Gradient Gaussian Approximation Filter with Positive Definiteness Guarantee
Tianyi Zhang, Wenhan Cao, Shengbo Eben Li
Popular Bayes filters often apply linearization techniques, such as Taylor expansion or stochastic linear regression, to enable the use of the Kalman filter structure, but this can…
eess.SY2025
Algorithm Design and Comparative Test of Natural Gradient Gaussian Approximation Filter
Wenhan Cao, Tianyi Zhang, Shengbo Eben Li
Popular Bayes filters typically rely on linearization techniques such as Taylor series expansion and stochastic linear regression to use the structure of standard Kalman filter. Th…
eess.SY2024
Nonlinear Bayesian Filtering with Natural Gradient Gaussian Approximation
Wenhan Cao, Tianyi Zhang, Zeju Sun +3
Practical Bayes filters often assume the state distribution of each time step to be Gaussian for computational tractability, resulting in the so-called Gaussian filters. When facin…