This paper achieves the synchronization of delayed neural networks (DNNs) considering aperiodic sampled-data control and communication delay. First of all, based on the master-slave DNNs with aperiodic sampling synchronization controller, a synchronization error system is constructed. Then, an augmented functional containing both the error state and its derivative is constructed. Compared with the existing researches, the augmented functional introduces more cross information of error states to the criterion. Next, an integral inequality based on the separation of internal integral variable and matrix is developed. Compared to the inequalities that treat the internal variable and the matrix as unified ones, the developed inequality provides a tighter estimate of the derivative of the augmented functional. On this basis, a criterion with less conservative is developed for the aperiodic sampled-data synchronization of DNNs considering communication delay. Finally, to indicate the superiority of the developed method on improving the acceptable sampling upper bound of synchronization, three numerical examples are provided.

中文翻译：

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考虑通信时延的基于矩阵分离的延迟神经网络非周期采样数据同步积分不等式


本文实现了考虑非周期采样数据控制和通信延迟的延迟神经网络（DNN）的同步。首先，基于具有非周期采样同步控制器的主从DNN，构建了同步误差系统。然后，构造一个包含错误状态及其导数的增广函数。与现有研究相比，增广函数在判据中引入了更多的错误状态交叉信息。接下来，提出了基于内部积分变​​量和矩阵分离的积分不等式。与将内部变量和矩阵视为统一的不等式相比，所开发的不等式提供了对增广函数的导数的更严格的估计。在此基础上，提出了考虑通信延迟的DNN非周期采样数据同步的保守性较低的准则。最后，为了表明所开发的方法在提高可接受的同步采样上限方面的优越性，提供了三个数值示例。