Exponential stability of impulsive stochastic fuzzy reaction-diffusion Cohen-Grossberg neural networks with mixed delays

  • Authors:
  • Changhong Wang;Yonggui Kao;Guowei Yang

  • Affiliations:
  • Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150001, PR China;Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150001, PR China and Shandong Provincial Key Laboratory of Industrial Control Technology, Qingdao Univ ...;College of Information Engineering, Nanchang Hangkong University, Nanchang 330063, PR China

  • Venue:
  • Neurocomputing
  • Year:
  • 2012

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Abstract

The problem of mean square exponential stability for a class of impulsive stochastic fuzzy Cohen-Grossberg networks with mixed delays and reaction-diffusion terms is investigated in this paper. By using the properties of ''M-cone'', eigenspace of the spectral radius of nonnegative matrices, Lyapunov functional, Ito's formula and inequality techniques, several sufficient conditions guaranteeing the mean square exponential stability of its equilibrium solution are obtained. These results extend and improve the earlier publications. Two examples are presented to illustrate the effectiveness and efficiency of the results.