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Parameter Estimation for Continuous Time Hidden Markov Processes

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Abstract

A survey of research works on the parameter estimation of hidden Markov processes is presented. Two observation models are considered: a partially observed two-dimensional Gaussian process and a telegraph process observed against the background of white Gaussian noise. The properties of estimators in the large sample and small noise asymptotics are described. Special attention is paid to the computational complexity and asymptotic efficiency of the estimators proposed.

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Authors and Affiliations

  1. Le Mans Université, Le Mans, France

    Yu. A. Kutoyants

  2. Tomsk State University, Tomsk, Russia

    Yu. A. Kutoyants

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  1. Yu. A. Kutoyants
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Correspondence to Yu. A. Kutoyants.

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This paper was recommended for publication by E. Ya. Rubinovich, a member of the Editorial Board

Russian Text © The Author(s), 2020, published in Avtomatika i Telemekhanika, 2020, No. 3, pp. 86–113.

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Kutoyants, Y.A. Parameter Estimation for Continuous Time Hidden Markov Processes. Autom Remote Control 81, 445–468 (2020). https://doi.org/10.1134/S0005117920030054

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  • DOI: https://doi.org/10.1134/S0005117920030054

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