具有不可微分时滞的四元数值Cohen-Grossberg神经网络的指数稳定性  

Exponential Stability of Quaternion-valued Cohen-Grossberg Neural Network Model with Non-differentiable Delays

作　　者：杨艳平 陈展衡 Yang Yangping;Chen Zhanheng(College of Mathematics and Statistics,Yili Normal University,Yining,Xinjiang 835000,China;Institute of Applied Mathematics,Yili Normal University,Yining,Xinjiang 835000,China)

机构地区：[1]伊犁师范大学数学与统计学院,新疆伊宁835000 [2]伊犁师范大学应用数学研究所,新疆伊宁835000

出　　处：《伊犁师范大学学报（自然科学版）》2022年第4期18-23,共6页Journal of Yili Normal University：Natural Science Edition

基　　金：国家自然科学基金资助项目(61663045)。

摘　　要：利用M-矩阵理论、同胚映射原理,以及向量李雅普诺夫函数方法,研究了具有不可微分时滞的四元数值Cohen-Grossberg神经网络系统平衡点的存在唯一性和指数稳定性.最后,通过数值仿真实验验证了结论的有效性和正确性.In this paper, the author considers the existence of uniqueness and exponential stability of the equilibrium point of the quaternion-valued Cohen-Grossberg neural network with non-differentiable delays by using M-matrix theory and the principle of homogeneous mapping and vectorial Lyapunov function method. Finally, the conclusions are proved to be correct by numerical simulation experiments.

关 键 词：四元数 C-G神经网络 指数稳定 M矩阵 

分 类 号：O175.13[理学—数学]