摘要
研究了一类具有非线性脉冲效应和混合时滞的神经网络的指数同步。通过李雅普洛夫稳定性理论和一些不等式方法,利用p-范数得到了新的指数同步的充分条件。和之前的脉冲效应是线性函数的结论相比较,消除了对线性脉冲效应系数γij∈[0,2]的限制,适用范围更广泛。
Exponential synchronization of neural networks with nonlinear impulsive γij∈[0,2]effects and mixed time delays was discussed. By Lyapunov stability theory and inequality techniques,some new and useful sufficient conditions on the exponential synchronization were obtained based on p-norm. Compared with recently years of linear impulsive effects results about neural networks synchronization,our results remove the restrictions that the impulsive gain γij∈[0,2],so our results are more general.
出处
《重庆理工大学学报（自然科学）》
CAS
2016年第9期143-150,共8页
Journal of Chongqing University of Technology：Natural Science
基金
国家自然科学基金资助项目(71461027)
贵州省计划科技项目(黔科合LH字[2015]7053号
黔科合LH字[2015]7005)
关键词
指数同步
神经网络
混合时滞
非线性脉冲效应
p-范数
exponential synchronization
neural network
mixed time delay
nonlinear impulsive effects
p-norm
