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This article is cited in 2 scientific papers (total in 2 papers)
Intellectual Control Systems, Data Analysis
Adaptive recognition of a Markov binary signal of a linear system based on the Pearson type I distribution
V. A. Bukhaleva, A. A. Skrynnikovbc, V. A. Boldinovc a Moscow Research Television Institute, Moscow, 105094 Russia
b State Research Institute of Aviation Systems (GosNIIAS), Moscow, 125167 Russia
c Moscow Aviation Institute, Moscow, 125993 Russia
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.
Keywords:
Pearson type I distribution, random jump structure, Markov binary signal, adaptive algorithm, transition probabilities of Markov chain.
Citation:
V. A. Bukhalev, A. A. Skrynnikov, V. A. Boldinov, “Adaptive recognition of a Markov binary signal of a linear system based on the Pearson type I distribution”, Avtomat. i Telemekh., 2022, no. 8, 159–168; Autom. Remote Control, 83:8 (2022), 1278–1287
Linking options:
https://www.mathnet.ru/eng/at16023 https://www.mathnet.ru/eng/at/y2022/i8/p159
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Abstract page: | 71 | References: | 14 | First page: | 11 |
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