Risk-sensitive filtering and smoothing for hidden Markov models

DOI10.1016/0167-6911(94)00093-BzbMath0877.93139MaRDI QIDQ672443

John B. Moore, Subhrakanti Dey

Publication date: 28 February 1997

Published in: Systems \& Control Letters (Search for Journal in Brave)

zbMATH Keywords

Hidden Markov modelFixed-interval smoothingInformation statereference probability methodRisk-sensitive filtering

Mathematics Subject Classification ID

Data smoothing in stochastic control theory (93E14) Optimal stochastic control (93E20)

Related Items (9)

Event-triggered smoothing for hidden Markov models: risk-sensitive and MMSE results ⋮ Risk-sensitive fixed-point smoothing estimation for linear discrete-time systems with multiple output delays ⋮ Event-triggered robust state estimation for systems with unknown exogenous inputs ⋮ An adaptive risk-sensitive filtering method for Markov jump linear systems with uncertain parameters ⋮ Risk‐sensitive filtering for nonlinear Markov jump systems on the basis of particle approximation ⋮ The Wonham filter under uncertainty: A game-theoretic approach ⋮ Minimax estimation in systems of observation with Markovian chains by integral criterion ⋮ Risk-sensitive probability for Markov chains ⋮ On asymptotic stability of continuous-time risk-sensitive filters with respect to initial conditions

Cites Work

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• Finite-dimensional quasi-linear risk-sensitive control
• Risk-sensitive linear/quadratic/gaussian control
• Recursive estimation from discrete-time point processes
• On-line estimation of hidden Markov model parameters based on the Kullback-Leibler information measure
• Risk-sensitive control and dynamic games for partially observed discrete-time nonlinear systems
• Statistical Inference for Probabilistic Functions of Finite State Markov Chains

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