摘要
研究了一类变时滞细胞神经网络平衡点的全局指数稳定性问题.在不要求激励函数全局Lipschitz条件下,利用Lyapunov函数方法和M-矩阵的特性,结合Young不等式和Halanay时滞微分不等式,得到了细胞神经网络模型在一定条件下全局指数稳定的一些充分条件.数值例子说明了本文结果的有效性.
The main purpose is to study the globally exponential stability of the equilibrium point for a class of cellular neural networks with variable delays. Without assuming global Lipschitz conditions on the activation functions, applying idea of vector Lyapunov function and the characteristic of the M-matrix, combining Young inequality and Halanay differential inequality with delay, some sufficient conditions for globally exponential stability of neural networks are obtained. As an illustration, a numerical example is worked out using the results obtained.
出处
《山东大学学报（理学版）》
CAS
CSCD
北大核心
2007年第4期58-62,共5页
Journal of Shandong University(Natural Science)
基金
国家自然科学基金资助项目(10461006)
烟台大学青年基金资助项目(JS05Z9)
关键词
细胞神经网络
变时滞
全局指数稳定性
cellular neural networks
variable delay
globally exponential stability
