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Synchronization of stochastic competitive neural networks with different timescales and reaction-diffusion terms
1School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu 611731, China cdycshi@163.com.
Abstract:
We propose a feedback controller for the synchronization of stochastic competitive neural networks with different timescales and reaction-diffusion terms. By constructing a proper Lyapunov-Krasovskii functional, as well as employing stochastic analysis theory, the LaShall-type invariance principle for stochastic differential delay equations, and a linear matrix inequality (LMI) technique, a feedback controller is designed to achieve the asymptotical synchronization of coupled stochastic competitive neural networks. A simulation example is given to show the effectiveness of the theoretical results.
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