随机时滞神经网络的全局指数稳定性

Globally exponential stability of stochastic neural networks with delay

首先对一般随机系统的渐近特性进行了讨论.然后结合神经网络的特点,应用李雅普诺夫第二方法对一类随机时滞神经网络系统的全局指数稳定性进行了分析,给出了易于判定随机时滞神经网络几乎必然指数稳定性新的代数判据,并给出实例进行仿真实验.

Firstly, the asymptotic property of general stochastic system is discussed, and then the global exponential stability of a class of stochastic neural networks with delay is analyzed by making use of the characteristic of neural network and the Lyapunov second method. New algebraic criteria that can be easily used to verify the almost exponential stability of the stochastic neural networks with delay are proposed. An example is given for illustration.