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一类具有变时滞的Hopfield型神经网络的全局指数稳定性
引用本文:孙建枝,武怀勤,单彩虹.一类具有变时滞的Hopfield型神经网络的全局指数稳定性[J].计算技术与自动化,2007,26(3):9-12.
作者姓名:孙建枝  武怀勤  单彩虹
作者单位:[1]燕山大学理学院,河北秦皇岛066004 [2]哈尔滨工业大学数学系,黑龙江哈尔滨150001
基金项目:国家自然科学基金资助项目(10571035).
摘    要:通过构造适当的Lyapunov函数,利用Halanay不等式和Young不等式,讨论一类具有变时滞的Hopfield型神经网络的全局指数稳定性.在对网络施加两个不同的神经元激励函数的条件下,导出网络全局指数稳定的一个充分条件,得到的充分条件在实际应用中易于验证,且有较小的保守性,因而对网络的应用和设计具有重要意义.最后,一个数值实例进一步验证结果的正确性.

关 键 词:神经网络  Halanay不等式  全局指数稳定性  变时滞  Hopfield  Neural  Networks  神经网络  指数稳定性  Delays  Exponential  Stability  结果  数值实例  意义  应用和设计  保守性  验证  充分条件  激励函数  神经元  Young  不等式  利用  Lyapunov  构造
文章编号:1003-6199(2007)03-0009-04
收稿时间:2007-06-22
修稿时间:2007-06-22

Global Exponential Stability for Hopfield Neural Networks with Varying Delays
SUN Jian-zhi,WU Huai-qin,SHAN Cai-hong.Global Exponential Stability for Hopfield Neural Networks with Varying Delays[J].Computing Technology and Automation,2007,26(3):9-12.
Authors:SUN Jian-zhi  WU Huai-qin  SHAN Cai-hong
Affiliation:1. College of Science, Yanshan University, Qinhuangdao 066004,China; 2. Department of Mathematics, Harbin Institute of technology, Harbin 150001, China
Abstract:In this paper, global exponential stability of Hopfield neural networks with time - varying delays is investigated by constructing suitable Lyapunov function and using Young inequality and Halanay inequality in connection with inequality analysis techniques , A new sufficient condition is obtained to guarantee global exponential stability of networks, The condition are easy to check in practice and impose less conservation. Thus, the obtained results possess importance significance in the application and design of networks, At last, an example is given to illustrate the application of our results.
Keywords:neural networks  global exponential stability  delays
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