Nonlinear filtering and identification algorithms for correlation-extremum dynamic systems with random structure
1Moscow Aviation Institute (National Research University), Moscow, Russia
Vibroengineering PROCEDIA, Vol. 8, 2016, p. 531-537.
Received 7 September 2016; accepted 13 September 2016; published 7 October 2016
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],  for their researches that stimulate further investigations.
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