湖南农业大学学报（自然科学版）2008，Vol.34Issue(3)：374-378,5.
不连续激励函数时滞Cohen-Grossberg神经网络的动力学性质
Regular dynamics in delayed Cohen-Grossberg neural networks with discontinuous activation functions
摘要
Abstract
A class of Cohen-Grossberg neural networks where the neuron activations are modeled by discontinuous functions was considered. A tool,the chain rule for computing the time derivative along the neural network solutions of a nondifferentiable Lyapunov function,is used which enables us to apply a Lyapunov-like approach to differential equations with discontinuous right-hand side. By means of the Lyapunov-like approach,a general result is proved on global exponential convergence toward a unique equilibrium point of the neural network solutions in the sense of Filippov.关键词
Cohen-Grossberg神经网络/全局指数稳定/非线性方法/M-矩阵Key words
Cohen-Grossberg neural networks/global exponential stability/nonlinear measure/M-matrix分类
数理科学引用本文复制引用
李绪孟,黄立宏,王小卉..不连续激励函数时滞Cohen-Grossberg神经网络的动力学性质[J].湖南农业大学学报（自然科学版）,2008,34(3):374-378,5.基金项目
Youth Science Foundation of HNAU(07QN17) （07QN17）
