一类随机离散神经网络全局渐近同步

Synchronization of a class of uncertain stochastic discrete-time delayed neural networks

研究离散型时滞随机神经网络的同步问题,考虑了参数不确定性,解决离散型分布时滞对神经网络同步问题的影响.基于主从同步的概念,设计一个有更广泛应用的控制器,应用Lyapunov稳定性理论和线性矩阵不等式工具箱,得到这类神经网络同步的充分性判据.最后给出实际例子,检验了判据的有效性.

The global asymptotical synchronization problem is discussed for a general class of uncertain stochastic discrete - time neural networks with time delay in this paper. Time delays include time - va- rying delay and distributed delay. A better controller is designed for synchronization. Based on the drive- response concept and the Lyapunov stability theorem, a linear matrix inequality （LMI） ap- proach is exploited to establish sufficient conditions under which the considered neural networks are globally asymptotically synchronized in the mean square.