基于全局Lipschitz连续激励函数方法探讨了带有时滞的变系数Hopfield神经网络模型,借助不动点和Lyapunov泛函数确保给定的神经网络的全局渐进稳定.
In this Letter, we discuss delayed Hopfield neural networks of variable coefficients and distribution, based on globally Lipschitz continuous activation functions, the equilibrium point and the Lyapunov functional method. Sufficient condition ensuring Globally symptotical Stability of neural networks are given.