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具有非线性脉冲效应的Cohen-Grossberg型神经网络的指数同步 被引量:1

Exponential Synchronization for Cohen-Grossberg Neural Networks with Nonlinear Impulsive Effects
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摘要 研究了一类具有非线性脉冲效应的Cohen-Grossberg型神经网络的指数同步,通过李亚普诺夫稳定性理论和一些不等式方法,利用r-范数得到了新的指数同步的充分条件;相对于线性脉冲效应文章中的结论,消除了对脉冲获得系数γik∈[-2,0]的限制,适用范围更加广泛一些。 In this paper,exponential synchronization for Cohen-Grossberg neural networks with nonlinear impulsive effects is discussed. By Lyapunov functinoal method and by utilizing inequality techniques,some new and useful sufficient conditions on the exponential synchronization are obtained based on r-norm. Compared with recent years of linear impulsive effects results about neural networks synchronization,our results remove the restrictions of the impulsive gain γik∈ [-2,0],so our results are more general.
出处 《重庆工商大学学报(自然科学版)》 2016年第3期1-5,共5页 Journal of Chongqing Technology and Business University:Natural Science Edition
基金 国家自然科学基金资助项目(71461027) 贵州省科技厅与遵义师范学院联合基金(黔科合LH字[2015]7053号 黔科合LH字[2015]7005 黔科合LH字[2015]7055号 黔科合LH字[2015]7007号) 昌吉职业技术学院自然科学科研课题(CJZY2015026)
关键词 Cohen-Grossberg型神经网络 非线性脉冲效应 变时滞 r-范数 指数同步 Cohen-Grossberg neural networks nonlinear impulsive effects time-varying delays r-norm exponential synchronization
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