带马尔可夫跳变和脉冲的时滞耦合神经网络的同步

On synchronization an array of impulsive coupled neural networks with Markovian jump and mixed time delays

研究一类混合时滞耦合神经网络的同步问题,其中系统及其参数的切换和时滞均由某个马尔可夫链所确定,同时考虑脉冲的影响.另外,对细胞激活函数进行更为一般的假设.通过构造Lyapunov-Krasovskii泛函,运用线性矩阵不等式技术(linear matrix inequality,LMI)并结合Kronecker积获得神经网络全局同步的充分性判据,且该判据依赖于时滞,易于利用数学软件Matlab的LMI工具箱进行验证和求解.

This paper investigates the global asymptotically synchronization problem for an array of coupled neural networks with mixed time delays and impulsive effects.The network switches from one mode to another,besides the parameters and time delays,according to a Markovian chain.And,the description of the activation functions is more general than the Lipschitz conditions.By employing Lyapunov-Krasovskii functional,and conducting a linear matrix inequality（LMI） approach,Kronecker product is developed to derive the criteria for the synchronization,which can be readily checked by using some standard numerical packages such as the Matlab LMI Toolbox.