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Robust identification of nonlinear objects with the help of an evolving radial basis network

Abstract

The problem of neural network-based robust identification of nonlinear dynamic objects in the presence of non-Gaussian noise is considered. To solve this problem, a radial basis network was chosen whose structure is specified and training is provided with the help of a genetic algorithm. The simulation results are presented that confirm the efficiency of the proposed approach.

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Correspondence to O. G. Rudenko.

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Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 15–26, March–April 2013.

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Rudenko, O.G., Bezsonov, O.O. & Rudenko, S.O. Robust identification of nonlinear objects with the help of an evolving radial basis network. Cybern Syst Anal 49, 173–182 (2013). https://doi.org/10.1007/s10559-013-9497-0

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Keywords

  • neural network
  • training
  • identification
  • evolutionary algorithm
  • robustness