具有随机扰动和Markov切换的中立型耦合神经网络的自适应同步  

Adaptive Synchronization of Neutral-Type Coupled Neural Networks With Stochastic Perturbations and Markovian Jumpings

作　　者：张志姝 高燕[1] ZHANG Zhishu;GAO Yan(School of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201600,P.R.China)

机构地区：[1]上海工程技术大学电子电气工程学院,上海201600

出　　处：《应用数学和力学》2020年第12期1381-1391,共11页Applied Mathematics and Mechanics

摘　　要：研究了具有时变时滞和随机扰动的中立型神经网络的自适应同步问题.随机扰动用Brown运动来描述.通过Lyapunov稳定性理论,利用了LMI分析技巧和矩阵理论,研究了具有随机扰动和Markov切换的中立型神经网络的自适应同步,给出并证明了使系统同步的充分条件,得出了具有时变时滞和随机扰动的中立型神经网络的自适应同步的判据.最后,给出数值例子来说明理论结果的有效性.The adaptive synchronization problem of neutral-type neural networks with time-varying delays and stochastic perturbations was discussed.Stochastic perturbations were described as the Brownian motion.Through the Lyapunov stability theory,the LMI analysis techniques and the matrix theory were used to study the adaptive synchronization of neutral-type neural networks with stochastic perturbations and Markovian jumpings.The sufficient conditions for the system synchronization were given and proved.The criterion for adaptive synchronization of neutral-type neural networks with time-varying delays and stochastic perturbations was obtained.Finally,numerical examples show the effectiveness and applicability of the proposed approach.

关 键 词：中立型神经网络 随机扰动 牵制控制 自适应同步 

分 类 号：O175[理学—数学]