Bayesian M-T clustering for reduced parameterisation of Markov chains used for nonlinear adaptive elements

DOI10.1016/S0005-1098(01)00060-7zbMath0979.93118OpenAlexW1990010869MaRDI QIDQ5939333

Elmawati L. Sutanto, Markéta Valečková, Miroslav Kárný

Publication date: 28 October 2001

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0005-1098(01)00060-7

zbMATH Keywords

system identificationMarkov chainsadaptive controlcluster algorithmBayesian estimationnonlinear stochastic systemsreduction of dimensionswitching modes

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Clustering in the social and behavioral sciences (91C20) Nonlinear systems in control theory (93C10) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Identification in stochastic control theory (93E12)

Related Items (1)

Recursive estimation of high-order Markov chains: approximation by finite mixtures

Cites Work

• Statistical decision theory and Bayesian analysis. 2nd ed
• Bayesian system identification
• Bayesian learning for neural networks
• Problems of identification and control
• Quantification of prior information revised
• On a general concept of forgetting
• Statistical analysis of finite mixture distributions
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