重庆工商大学学报（自然科学版）2017，Vol.34Issue(1)：21-26,6.DOI:10.16055/j.issn.1672-058X.2017.0001.005
分数阶BAM神经网络的全局渐进稳定性
Global Asymptotic Stability of Fractional-order BAM Neural Networks
李倩 1李东 1王娴1
作者信息
- 1. 重庆大学 数学与统计学院，重庆401331
- 折叠
摘要
Abstract
This paper studies the unique existence and global asymptotic stability of the equilibrium point of fractional-order BAM neural networks,obtains the sufficient condition for the unique existence of the systematic equilibrium point by using contraction mapping principle,receives the sufficient condition of the global asymptotic stability of the equilibrium point of the studied model by constructing Lyapunov function and by using Lyapunov function theory,matrix inequality method and Laplace integral transform method,gives more strict and easier verification condition by the form of matrix inequalities and verifies the correctness of the conclusion by numerical simulation.关键词
分数阶/BAM神经网络/压缩映像原理/矩阵不等式/Laplace积分变换Key words
fractional-order/BAM neural network/contraction mapping principle/matrix inequality/Laplace integral transform引用本文复制引用
李倩,李东,王娴..分数阶BAM神经网络的全局渐进稳定性[J].重庆工商大学学报（自然科学版）,2017,34(1):21-26,6.
