具有时变时滞的复值BAM神经网络的概周期解  

The Almost Periodic Solution of Complex-valued BAM Neural Networks with Time-varying Delays

作　　者：赵莉莉 ZHAO Lili(School of Mathematics and Statistics,Yunnan University,Kunming 650091,China)

机构地区：[1]云南大学数学与统计学院,云南昆明650091

出　　处：《滨州学院学报》2024年第2期52-62,共11页Journal of Binzhou University

基　　金：云南省教育厅自然科学基金项目(2020J0020);云南大学教育教学改革基金项目(2023Y22)。

摘　　要：研究了一类具有时变时滞的复值BAM神经网络,利用Banach空间中的不动点定理、实数集上的指数二分性,以及若干微分不等式技巧,获得了该类复值神经网络的概周期解存在、唯一,以及一致稳定的充分条件。最后,通过实例验证了所得结果的有效性与可行性。In this paper,a class of complex-valued BAM neural networks with time-varying delays is studied.By using the Fixed-point theorem in Banach spaces,the exponential dichotomy on the set of real numbers,and some techniques of differential inequalities,sufficient conditions for the existence,uniqueness and uniform stability of almost periodic solutions of the complex-valued neural networks are obtained.Finally,an example is given to verify the validity and feasibility of the results.

关 键 词：复值神经网络 BAM神经网络 概周期解 不动点定理 一致稳定性 

分 类 号：O175[理学—数学]