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Analysis of Exponential Stability for Neutral Stochastic Cohen-Grossberg Neural Networks with Mixed Delays

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  • Tianqing Yang
  • Zuoliang Xiong
  • Cuiping Yang

Abstract

This paper is concerned with the mean-square exponential input-to-state stability problem for a class of stochastic Cohen-Grossberg neural networks. Different from prior works, neutral terms and mixed delays are discussed in our system. By employing the Lyapunov-Krasovskii functional method, Itô formula, Dynkin formula, and stochastic analysis theory, we obtain some novel sufficient conditions to ensure that the addressed system is mean-square exponentially input-to-state stable. Moreover, two numerical examples and their simulations are given to illustrate the correctness of the theoretical results.

Suggested Citation

  • Tianqing Yang & Zuoliang Xiong & Cuiping Yang, 2019. "Analysis of Exponential Stability for Neutral Stochastic Cohen-Grossberg Neural Networks with Mixed Delays," Discrete Dynamics in Nature and Society, Hindawi, vol. 2019, pages 1-15, June.
    • Handle: RePEc:hin:jnddns:4813103
    DOI: 10.1155/2019/4813103
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