Identification of Gaussian process with switching noise mode and missing data

DOI10.1016/j.jfranklin.2021.03.015zbMath1465.93221OpenAlexW3142921405MaRDI QIDQ2030947

Fan Guo, Biao Huang, Lei Chen, Wentao Bai, Kuang-Rong Hao

Publication date: 8 June 2021

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2021.03.015

zbMATH Keywords

system identificationGaussian white noiseswitching Gaussian noise

Mathematics Subject Classification ID

Identification in stochastic control theory (93E12) White noise theory (60H40)

Cites Work

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• Output feedback stabilization of stochastic feedforward systems with unknown control coefficients and unknown output function
• EM algorithm-based identification of a class of nonlinear Wiener systems with missing output data
• On the convergence properties of the EM algorithm
• Stability analysis of semi-Markov switched stochastic systems
• Laplace approximation and natural gradient for Gaussian process regression with heteroscedastic Student-\(t\) model
• Distributed Student's t filtering algorithm for heavy‐tailed noises
• Stabilization of Stochastic Nonlinear Delay Systems With Exogenous Disturbances and the Event-Triggered Feedback Control
• Some Improved Razumikhin Stability Criteria for Impulsive Stochastic Delay Differential Systems
• A Bayesian approach to some outlier problems

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