Adaptive recognition of a Markov binary signal of a linear system based on the Pearson type I distribution

We consider the problem of finding the distribution law for the output signal of an aperiodic link whose input is acted upon by a random jump signal in the form of a Markov chain with two states. It has been theoretically proved that the probability density of the output signal is described by the Pearson type I distribution; this is experimentally confirmed by the results of mathematical modeling. The results obtained are used to synthesize an adaptive recognition algorithm for unknown transition probabilities in a Markov chain.