Abstract
Using the methods of the theory of optimal nonlinear filtering, we develop an algorithm for obtaining optimal estimates of the sequence of hidden states of discrete-valued Markov processes with abruptly changing parameters at unknown time. Optimal estimates of the states of Markov processes and of the time of appearance of an abrupt change in parameters are obtained as a result of interpolation by processing the entire observation sequence. The results of simulation of the algorithm work are presented.
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