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Exponential Synchronization of Stochastic Fuzzy Cellular Neural Networks with Reaction-Diffusion Terms via Periodically Intermittent Control

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Abstract

This paper considers the exponential synchronization of stochastic fuzzy cellular neural networks with time-varying delays and reaction-diffusion terms based on p-norm. Motivated by the achievements from both the stability of fuzzy cellular neural networks with stochastic perturbation and reaction-diffusion effects and the synchronization issue of coupled chaotic delayed neural networks by using periodically intermittent control approach, a periodically intermittent controller is proposed to guarantee the exponential synchronization of the coupled chaotic neural networks by using Lyapunov stability theory and stochastic analysis approaches. The synchronization results presented in this paper generalize and improve many known results. This paper also presents an illustrative example and uses simulated results of this example to show the feasibility and effectiveness of the proposed scheme.

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Authors and Affiliations

  1. Department of Basic Science, Shijiazhuang Mechanical Engineering College, Shijiazhuang, 050003, People’s Republic of China

    Qintao Gan

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  1. Qintao Gan
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Correspondence to Qintao Gan.

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Gan, Q. Exponential Synchronization of Stochastic Fuzzy Cellular Neural Networks with Reaction-Diffusion Terms via Periodically Intermittent Control. Neural Process Lett 37, 393–410 (2013). https://doi.org/10.1007/s11063-012-9254-9

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  • DOI: https://doi.org/10.1007/s11063-012-9254-9

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