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Synchronization of stochastic chaotic neural networks with reaction-diffusion terms

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Abstract

In this paper, we are concerned with the synchronization problem of a class of stochastic reaction-diffusion neural networks with time-varying delays and Dirichlet boundary conditions. By using the Lyapunov–Krasovskii functional method, feedback control approach and stochastic analysis technology, delay-dependent synchronization conditions including the information of reaction-diffusion terms are presented, which are expressed in terms of linear matrix inequalities (LMIs). The feedback controllers can be constructed by solving the derived LMIs. Finally, illustrative examples are given to show the effectiveness of the proposed technique.

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Authors and Affiliations

  1. School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, P.R. China

    Qian Ma, Shengyuan Xu & Yun Zou

  2. School of Information Science and Engineering, Changzhou University, Changzhou, 213164, P.R. China

    Guodong Shi

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  1. Qian Ma
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  2. Shengyuan Xu
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  3. Yun Zou
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  4. Guodong Shi
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Correspondence to Shengyuan Xu.

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Ma, Q., Xu, S., Zou, Y. et al. Synchronization of stochastic chaotic neural networks with reaction-diffusion terms. Nonlinear Dyn 67, 2183–2196 (2012). https://doi.org/10.1007/s11071-011-0138-8

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  • DOI: https://doi.org/10.1007/s11071-011-0138-8

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