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具有变系数和变时滞的BAM神经网络的全局指数稳定性的新判据
引用本文:关朋,黄元清.具有变系数和变时滞的BAM神经网络的全局指数稳定性的新判据[J].四川轻化工学院学报,2010(6):643-647.
作者姓名:关朋  黄元清
作者单位:[1]电子科技大学数学科学学院,成都610054 [2]四川理工学院计算机学院,四川自贡643000
基金项目:国家973项目资助(2010CB732501)
摘    要:研究了一类具有变系数和变时滞的联想记忆神经网络的全局指数稳定性。通过选择适当的Lyapunov—krasovskii泛函,利用不等式技巧给出了联想记忆神经网络的全局指数稳定性的新判据。

关 键 词:BAM神经网络  Lyapunov—krasovskii泛函  全局指数稳定  线性矩阵不等式

New Criteria of Global Exponential Stability of BAM Neural Networks with Variable Coefficients and Time-Varying Delays
GUAN Peng,HUANG Yuan-qing.New Criteria of Global Exponential Stability of BAM Neural Networks with Variable Coefficients and Time-Varying Delays[J].Journal of Sichuan Institute of Light Industry and Chemical Technology,2010(6):643-647.
Authors:GUAN Peng  HUANG Yuan-qing
Affiliation:1. School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu 610054, 2. School of Computer Science, Sichuan University of Science & Engineering, Zigong 643000, China)
Abstract:The global exponential stability problem of a class of variable coefficients and variable delays of the BAM neural network is studied. By choosing appropriate Lyapunov-Krasovskii functional and applying linear matrix inequality technique, the new criterias of global exponential stability of BAM neural networks are obtained.
Keywords:BAM neural network  Lyapunov-Krasovskii functional  global exponential stability  linear matrix inequality
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