Covergence of stochastic fuzzy Cohen-Grossberg neural networks with reaction-diffusion and distributed delays

  • Authors:
  • Liping Chen;Yi Chai;Ranchao Wu

  • Affiliations:
  • School of Automation, Chongqing University, Chongqing 400030, China;School of Automation, Chongqing University, Chongqing 400030, China;School of Mathematics, Anhui University, Hefei 230039, China

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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Abstract

In this paper, a class of stochastic fuzzy Cohen-Grossberg neural networks with reaction-diffusion and distributed delays is discussed. Based on Lyapunov functionals, inequality analysis, Ito's formula, nonnegative semimartingale convergence theorem and stochastic analysis, some stability sufficient conditions are presented to guarantee the neural networks to be almost sure and mean square exponentially stable, respectively. The proposed results improve and extend some earlier literature and are easier to verify. For illustration, an example is given to illustrate the feasibility of the results.