时标上一类时滞BAM神经网络的伪概周期解  

Pseudo Almost Periodic Solutions for a Class of Delayed BAM Neural Networks on Time Scales

作　　者：林清梅[1] 张雪梅[2] 蒋建新[1] LIN Qingmei ZHANG Xuemei JIANG Jianxin(School of Mathematics, Wenshan University, Wenshan Yunnan 663099, China School of Mathematics and Information Science, Qujing Normal University, Qujing Yunnan 655011, China)

机构地区：[1]文山学院数学学院,云南文山663099 [2]曲靖师范学院数学与信息科学学院,云南曲靖655011

出　　处：《文山学院学报》2016年第6期48-52,共5页Journal of Wenshan University

基　　金：文山学院科研基金项目"时标上时滞神经网络的概周期解研究"(15WSY13)

摘　　要：研究了时标上一类具有分布型泄露项时滞的中立型BAM神经网络的伪概周期解的存在性和全局指数稳定性。利用指数二分性理论、压缩映射原理、不动点理论和李雅普诺夫函数法,得到了该系统的伪概周期解的存在性和全局指数稳定性的充分条件。In this paper, a class of neutral type BAM neural networks model with distributed leakage delays on time scales is discussed. Some sufficient conditions are established for the existence and global exponential stability of the pseudo almost periodic solutions to the considered model using exponential dichotomy theory, contraction mapping principle, fixed point theorem and Lyapunov functional method.

关 键 词：时标 伪概周期解 存在性 全局指数稳定性 

分 类 号：O177[理学—数学]