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Synchronization of Neural Networks With Control Packet Loss and Time-Varying Delay via Stochastic Sampled-Data Controller

机译:通过随机采样数据控制器同步具有控制包丢失和时变时延的神经网络

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This paper addresses the problem of exponential synchronization of neural networks with time-varying delays. A sampled-data controller with stochastically varying sampling intervals is considered. The novelty of this paper lies in the fact that the control packet loss from the controller to the actuator is considered, which may occur in many real-world situations. Sufficient conditions for the exponential synchronization in the mean square sense are derived in terms of linear matrix inequalities (LMIs) by constructing a proper Lyapunov–Krasovskii functional that involves more information about the delay bounds and by employing some inequality techniques. Moreover, the obtained LMIs can be easily checked for their feasibility through any of the available MATLAB tool boxes. Numerical examples are provided to validate the theoretical results.
机译:本文解决了具有时变时延的神经网络的指数同步问题。考虑具有随机变化的采样间隔的采样数据控制器。本文的新颖性在于考虑了从控制器到执行器的控制数据包丢失的情况,这可能发生在许多实际情况中。通过构造一个适当的Lyapunov-Krasovskii泛函,该泛函涉及延迟边界的更多信息,并采用一些不等式技术,可以根据线性矩阵不等式(LMI)得出均方指数同步的充分条件。此外,可以通过任何可用的MATLAB工具箱轻松检查获得的LMI的可行性。数值例子验证了理论结果。

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