Article

Neural Processing Letters

, Volume 26, Issue 3, pp 191-200

First online:

pth Moment Exponential Stability of Stochastic Cohen-Grossberg Neural Networks With Time-varying Delays

  • Enwen ZhuAffiliated withSchool of Mathematics and Computing Sciences, Changsha University of Science and Technology Email author 
  • , Haomin ZhangAffiliated withSchool of Mathematics, Central South University
  • , Yong WangAffiliated withDepartment of Mathematics, Harbin Institute of Technology
  • , Jiezhong ZouAffiliated withSchool of Mathematics, Central South University
  • , Zheng YuAffiliated withSchool of Mathematics, Central South University
  • , Zhenting HouAffiliated withSchool of Mathematics, Central South University

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Abstract

The pth moment exponential stability of stochastic Cohen-Grossberg with time-varying delays is investigated in this paper. A set of novel sufficient conditions on pth moment exponential stability are given for the considered system by using the well-known Razumikhin-type theorem. Finally, two examples with their numerical simulations are provided to show the correctness of our analysis.

Keywords

Stochastic Cohen-Grossberg neural networks pth moment exponential stability Razumikhin-type theorem

Mathematics Subject Classifications (2000)

92B20 93E15 34K50