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Stability Analysis of Stochastic Fuzzy Cellular Neural Networks With Time-Varying Delays and Reaction-Diffusion Terms

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Abstract

In this paper, a class of stochastic fuzzy cellular neural networks with time-varying delays and reaction-diffusion terms is investigated. By using Lyapunov–Krasovskii functional and stochastic analysis approaches, new and less conservative delay-derivative-dependent stability criteria are presented to guarantee the neural networks to be globally exponentially stable in the mean square for all admissible stochastic perturbations. Numerical simulations are carried out to illustrate the main results.

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Authors and Affiliations

  1. Institute of Applied Mathematics, Shijiazhuang Mechanical Engineering College, 97 Heping West Road, Shijiazhuang, 050003, Hebei Province, People’s Republic of China

    Qintao Gan, Rui Xu & Pinghua Yang

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  1. Qintao Gan
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  2. Rui Xu
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  3. Pinghua Yang
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Correspondence to Qintao Gan.

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Gan, Q., Xu, R. & Yang, P. Stability Analysis of Stochastic Fuzzy Cellular Neural Networks With Time-Varying Delays and Reaction-Diffusion Terms. Neural Process Lett 32, 45–57 (2010). https://doi.org/10.1007/s11063-010-9144-y

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  • DOI: https://doi.org/10.1007/s11063-010-9144-y

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