Robust synchronisation of uncertain chaotic neural networks with time-varying delay via stochastic sampled-data controller

This paper addresses the robust synchronization problem for chaotic neural networks with time-varying delay and parameter uncertainties. For simplicity, assuming two different sampling intervals whose happening probabilities satisfy Bernoulli distribution and are known constants. The sampling system is changed into a continuous system by employing an input delay scheme. Sufficient conditions for the robust mean-square synchronization are proved by constructing a proper Lyapunov functional. In addition, it is easily to validated the obtained results for their feasibility via MATLAB and other tool boxes. One simulation example is applied to show the effectiveness of proposed results.

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