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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