Nonlinear filtering and identification algorithms for correlation-extremum dynamic systems with random structure

Tatiana Kolosovskaya1

1Moscow Aviation Institute (National Research University), Moscow, Russia

1Corresponding author

Vibroengineering PROCEDIA, Vol. 8, 2016, p. 531-537.
Received 7 September 2016; accepted 13 September 2016; published 7 October 2016

Copyright © 2016 JVE International Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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The problem of adaptive estimation using spatial-time-varying filtering in dynamic systems with random structure is investigated. The proposed approach of the extension of state estimation in the classical stochastic dynamic systems with deterministic structure to the case of signal processing and parameter identification in stochastic systems with random structure or with switching parameters using the correlation-extremum methods and the theory of Markov processes provides the system operation in varying and uncertain external conditions.

Keywords: signal processing, filtering, identification, Markov processes, optimization of stochastic systems with random structure.


The author would like to thank the mentioned authors [1-3], [5] for their researches that stimulate further investigations.


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