具有变时滞离散Cohen-Grossberg神经网络的周期解  

Periodic Solutions of a Discrete-time Cohen-Grossberg-type Neural Networks with Varying Delays

作　　者：刘启明[1] 杨建法[2] 吴辰余[3] 

机构地区：[1]军械工程学院基础部,河北石家庄050003 [2]石家庄铁道职业技术学院基础部,河北石家庄050043 [3]邯郸学院数学系,河北邯郸056000

出　　处：《河北师范大学学报（自然科学版）》2010年第6期621-624,630,共5页Journal of Hebei Normal University：Natural Science

基　　金：国家自然科学基金(11071254)

摘　　要：讨论了具有变时滞离散Cohen-Grossberg神经网络模型,利用M-矩阵理论与适合Lypunov函数,得到该类模型周期解的存在性与全局指数稳定性,推广了先前的结果.A discrete-time Cohen-Grossberg neural networks with time-varying delays is investigated by using suitable Lypunov functional and the properties of M-matrix.Sufficient conditions to guarantee the uniqueness and global exponential stability of the periodic solution of such networks are established.The proposed results improve some earlier publications.

关 键 词：COHEN-GROSSBERG神经网络 离散时刻 时滞 周期解 指数稳定性 

分 类 号：O175.13[理学—数学]