具有广义时滞的神经网络滞后同步分析  

Lag Synchronization Analysis of Neural Networks with Generalized Delay

作　　者：裴萍[1] 韩思雨 卞继承[1] 黄达[1] 薛婷婷[1] PEI Ping;HAN Siyu;BIAN Jicheng;HUANG Da;XUE Tingting(College of Mathematics and Science,Xinjiang Institute of Engineering,Urumqi Xinjiang 830023,China)

机构地区：[1]新疆工程学院数理学院,新疆乌鲁木齐830023

出　　处：《新疆大学学报（自然科学版）（中英文）》2023年第4期414-421,432,共9页Journal of Xinjiang University(Natural Science Edition in Chinese and English)

基　　金：新疆维吾尔自治区自然科学基金“基于多层图结构下的多智能体网络的一致性研究”(2022D01A247).

摘　　要：研究了具有广义时滞的神经网络滞后同步问题.首先,提出了一类包含离散时滞和比例时滞的一阶神经网络模型.其次,通过对一阶神经网络设计反馈控制策略,利用Lyapunov泛函理论和Barbalat引理,给出了驱动-响应神经网络的滞后同步条件.最后,通过3个数值实例来验证理论结果的有效性.The lag synchronization problem of a class of neural networks with generalized delays is studied.Firstly,a class of first-order neural network models including discrete delays and proportional delays are proposed.Secondly,by designing a feedback control strategy for the first-order neural system,using the Lyapunov functional theory and the Barbarat lemma,the lag synchronization condition of the drive-response neural network is given.Finally,three numerical examples are given to verify the validity of the theoretical results.

关 键 词：神经网络 广义时滞 滞后同步 线性反馈控制 

分 类 号：O175.2[理学—数学] TP183[理学—基础数学]