具有变耦合时滞的离散时间神经网络的同步

Global Synchronization in an Array of Discrete-time Delayed Neural Networks with Time-varying Delayed Coupling

本文讨论一类具有变耦合时滞的离散时间神经网络的同步问题,通过构造Lyapunov-Krasovskii泛函,利用线性矩阵不等式(LMI),并结合Kronecker积来获得离散时间耦合神经网络全局指数同步的判据,所获得的判据依赖于时滞。该判据易于用MATLAB的LMI工具箱进行求解和验证,同时,对细胞激活函数做了更为一般的假设。

This paper discusses an array of discrete - time delayed neural networks with time - varying delayed coupling, and also, by employing Lyapunov - Krasovskii functional, and conducting a linear matrix inequality （LMI） approach, Kronecker prod- uct is developed to derive the criteria for the synchronization, which can be readily checked by using some standard numerical packages such as the MATLAB. Furthermore, the description of the activation functions is more general then the Lipsohitz condi- tions. And the criteria of synchronization are therefore less conservative.