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Mean almost periodicity and moment exponential stability of semi-discrete random cellular neural networks with fuzzy operations

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  • Sufang Han
  • Guoxin Liu
  • Tianwei Zhang

Abstract

By using the semi-discretization technique of differential equations, the discrete analogue of a kind of cellular neural networks with stochastic perturbations and fuzzy operations is formulated, which gives a more accurate characterization for continuous-time models than that by Euler scheme. Firstly, the existence of at least one p-th mean almost periodic sequence solution of the semi-discrete stochastic models with almost periodic coefficients is investigated by using Minkowski inequality, Hölder inequality and Krasnoselskii’s fixed point theorem. Secondly, the p-th moment global exponential stability of the semi-discrete stochastic models is also studied by using some analytical skills and the proof of contradiction. Finally, a problem of stochastic stabilization for discrete cellular neural networks is studied.

Suggested Citation

  • Sufang Han & Guoxin Liu & Tianwei Zhang, 2019. "Mean almost periodicity and moment exponential stability of semi-discrete random cellular neural networks with fuzzy operations," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-27, August.
  • Handle: RePEc:plo:pone00:0220861
    DOI: 10.1371/journal.pone.0220861
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