变系数变时滞BAM神经网络概周期解的存在性与全局吸引性(英文)  

Existence and Global Attractivity of Almost Periodic Solution for BAM Neural Networks with Variable Coefficients and Delays

作　　者：张丽娟[1] 

机构地区：[1]海军航空工程学院应用数学研究所

出　　处：《生物数学学报》2007年第3期403-412,共10页Journal of Biomathematics

基　　金：This Work was Supported by Distinguished Expert Science Foundation of Naval Aeronautical Institute and the Younger Foundation of Yantai University (SX06Z9)

摘　　要：利用指数二分性、Banach不动点定理与微分不等式分析技巧,在不要求激活函数有界的条件下,给出了变系数变时滞的BAM神经网络概周期解的存在唯一性和全局吸引性的充分条件.所得结果推广和改进了相应文献的结果,对设计BAM神经网络概周期振荡有重要意义.By using exponential dichotomy, the Banach fixed point theory and some inequality analysis technology, some sufficient conditions are derived ensuring existence, uniqueness and global attractivity of almost periodic solution for BAM neural networks with variable coefficients and delays. Without assuming the boundedness of signal function, these results obtained are significant in design and applications of almost periodic oscillatory BAM neural networks. We extend and improve previously known results.

关 键 词：BAM神经网络 概周期解 全局吸引性 指数二分性 不动点定理 

分 类 号：O175.14[理学—数学]