Existence and Exponential Stability of Almost Periodic Solutions to General BAM Neural Networks with Leakage Delays on Time Scales  

时间尺度上具有泄漏时滞的一般BAM神经网络概周期解的存在性和指数稳定性

作　　者：DONG Yan-shou HAN Yan DAI Ting-ting 董延寿;韩艳;代婷婷(School of Mathematics and Statistics,Zhaotong University,Zhaotong 657000,China)

机构地区：[1]School of Mathematics and Statistics,Zhaotong University,Zhaotong 657000,China

出　　处：《Chinese Quarterly Journal of Mathematics》2022年第2期189-202,共14页数学季刊（英文版）

基　　金：Partially supported by the Special Basic Cooperative Research Programs of Yunnan Provincial Undergraduate Universities'Association(Grant No.202101BA070001-045).

摘　　要：In this paper, the existence of almost periodic solutions to general BAM neural networks with leakage delays on time scales is first studied, by using the exponential dichotomy method of linear differential equations and fixed point theorem. Then, the exponential stability of almost periodic solutions to such BAM neural networks on time scales is discussed by utilizing differential inequality. Finally, an example is given to support our results in this paper and the results are up-to-date.

关 键 词：Almost periodic solution Neural network Time scale Leakage delay Existence and exponential stability 

分 类 号：O193[理学—数学]