IEEE Access (Jan 2023)

Robustness Analysis of Fuzzy Cellular Neural Network With Deviating Argument and Stochastic Disturbances

  • Fang Wenxiang,
  • Xie Tao,
  • Li Biwen

DOI
https://doi.org/10.1109/ACCESS.2023.3233946
Journal volume & issue
Vol. 11
pp. 3717 – 3728

Abstract

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Robustness analysis of fuzzy cellular neural networks with deviating arguments and stochastic disturbances is the main topic of discussion in this paper. The issue at hand is what the upper bounds of the disturbances and deviating intervals for the fuzzy cellular neural network can withstand before losing its stability. We solve these problems by using Gronwall-Bellman lemma and some inequality techniques. The theoretical results point that for an exponentially stable fuzzy cellular neural network, the perturbed fuzzy cellular neural network still keep its globally exponential stability if the upper bound of the length of deviating intervals or the intensity of stochastic disturbances is less than the upper bound derived in this paper. A number of numerical cases are offered to support the availability of conjectural values.

Keywords