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The stability of impulsive stochastic Cohen–Grossberg neural networks with mixed delays and reaction–diffusion terms

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Abstract

The global asymptotic stability of impulsive stochastic Cohen–Grossberg neural networks with mixed delays and reaction–diffusion terms is investigated. Under some suitable assumptions and using Lyapunov–Krasovskii functional method, we apply the linear matrix inequality technique to propose some new sufficient conditions for the global asymptotic stability of the addressed model in the stochastic sense. The mixed time delays comprise both the time-varying and continuously distributed delays. The effectiveness of the theoretical result is illustrated by a numerical example.

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Acknowledgments

This publication was made possible by NPRP (Grant No. 4-1162-1-181) from the Qatar National Research Fund (a member of Qatar Foundation). This work was also supported by Natural Science Foundation of China (Grant No. 61374078, 61403313).

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Authors and Affiliations

  1. College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, China

    Jie Tan & Chuandong Li

  2. College of Mathematics and Physics, Chongqing University of Science and Technology, Chongqing, 401331, China

    Jie Tan

  3. Texas A&M University at Qatar, Doha, Qatar

    Tingwen Huang

Authors
  1. Jie Tan
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  2. Chuandong Li
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  3. Tingwen Huang
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Correspondence to Chuandong Li.

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Tan, J., Li, C. & Huang, T. The stability of impulsive stochastic Cohen–Grossberg neural networks with mixed delays and reaction–diffusion terms. Cogn Neurodyn 9, 213–220 (2015). https://doi.org/10.1007/s11571-014-9316-y

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  • DOI: https://doi.org/10.1007/s11571-014-9316-y

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