Robust Neuroevolutionary Identification of Nonlinear Nonstationary Objects

Authors:
O. G. Rudenko;O. O. Bezsonov
Affiliations:
Kharkiv National University of Radioelectronics, Kharkiv, Ukraine;Kharkiv National University of Radioelectronics, Kharkiv, Ukraine
Venue:
Cybernetics and Systems Analysis
Year:
2014

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Abstract

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.