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Robust Neuroevolutionary Identification of Nonlinear Nonstationary Objects


The neuroevolutionary approach is proposed to construct mathematical models of nonlinear nonstationary objects under non-Gaussian noise. The general structure of an evolutionary feed-forward neural network is considered. The modeling of various cases of nonstationarity has proved the efficiency of the proposed approach.

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Correspondence to O. O. Bezsonov.

Additional information

Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 21–36, January–February 2014.

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Rudenko, O.G., Bezsonov, O.O. Robust Neuroevolutionary Identification of Nonlinear Nonstationary Objects. Cybern Syst Anal 50, 17–30 (2014).

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  • identification
  • robustness
  • nonlinear nonstationary object
  • artificial neural network
  • evolutionary calculation
  • genetic algorithm