反应扩散BAM神经网络的全局指数稳定性

Global Exponential Stability of Reaction-Diffusion BAM Neural Networks

利用拓扑度技巧、M-矩阵和变分理论,得到了考虑扩散因素在内的双向联想记忆人工神经网络系统的全局指数稳定性判定定理.结果表明,所给判据得出的指数稳定收敛速率估计比传统结果更精细.

A global exponential stability judging theorem was given via topological degree technique, M-matrix theory and variational methods, in which the reaction-diffusion item is considered. Our estimation of the convergent rate is more accurate than that of traditional estimation, and a numerical example shows the efficiency of the theorem.