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Adaptive Recognition of a Markov Binary Signal of a Linear System Based on the Pearson Type I Distribution

  • INTELLECTUAL CONTROL SYSTEMS, DATA ANALYSIS
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Abstract

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.

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Funding

This work was supported by the Russian Science Foundation, project no. 22-29-00708.

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Authors and Affiliations

  1. Moscow Research Television Institute, Moscow, 105094, Russia

    V. A. Bukhalev

  2. State Research Institute of Aviation Systems (GosNIIAS), Moscow, 125167, Russia

    A. A. Skrynnikov

  3. Moscow Aviation Institute, Moscow, 125993, Russia

    A. A. Skrynnikov & V. A. Boldinov

Authors
  1. V. A. Bukhalev
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  2. A. A. Skrynnikov
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  3. V. A. Boldinov
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Corresponding authors

Correspondence to V. A. Bukhalev, A. A. Skrynnikov or V. A. Boldinov.

Additional information

Translated by V. Potapchouck

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Bukhalev, V.A., Skrynnikov, A.A. & Boldinov, V.A. Adaptive Recognition of a Markov Binary Signal of a Linear System Based on the Pearson Type I Distribution. Autom Remote Control 83, 1278–1287 (2022). https://doi.org/10.1134/S0005117922080094

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  • DOI: https://doi.org/10.1134/S0005117922080094

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