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  

New Criteria of Global Exponential Stability of BAM Neural Networks with Variable Coefficients and Time-Varying Delays

作　　者：关朋[1] 黄元清[2] 

机构地区：[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

出　　处：《四川理工学院学报（自然科学版）》2010年第6期643-647,共5页Journal of Sichuan University of Science & Engineering(Natural Science Edition)

基　　金：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。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.

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 

分 类 号：O231[理学—运筹学与控制论]