Asymptotic Behavior of a Discrete-time Network Model of Two Neurons  

一类二元离散神经网络模型的渐近性(英文)

作　　者：朱惠延[1] 黄立宏[2] 

机构地区：[1]南华大学数理学院,湖南衡阳421001 [2]湖南大学数学与计量经济学院,湖南长沙410082

出　　处：《Journal of Mathematical Research and Exposition》2004年第2期267-272,共6页数学研究与评论（英文版）

基　　金：Supported by National Natural Science Foundation of China (10071016), the Key Research Program of Science and Technology of the Ministry of Education of China, the Doctor Program Foundation of the Ministry of Education of China(20010532002) and Foundatio

摘　　要：This paper is concerned with a delay difference systems arising from an arti-ficial network model of two neurons with piecewise coustant nonlinearity. The differencesystems can be regarded as the discrete analog of the artificial neural network of twoncurons. Some interesting results are obtained for the asymptotic behavior of solutionsof the systems.本文考虑的是一类具有分段常数非线性时滞差分系统,该系统可作为二元人工神经网络模型的离散形式,本文得到了系统解的渐近性的一些结果。

关 键 词：Neural networks asymptotic behavior difference system piecewise constant nonlinearity 

分 类 号：O29[理学—应用数学]