Quasi-synchronization control of quaternion-valued fuzzy memristive neural networks

被引：8

作者：

Li, Ruoxia ^{[1
]}

Cao, Jinde ^{[2
,3
]}

Li, Ning ^{[4
]}

机构：

[1] Shaanxi Normal Univ, Sch Math & Stat, Xian 710062, Peoples R China

[2] Southeast Univ, Sch Math, Nanjing 210096, Peoples R China

[3] Yonsei Univ, Yonsei Frontier Lab, Seoul 03722, South Korea

[4] Henan Univ Econ & Law, Coll Math & Informat Sci, Zhengzhou 450046, Henan, Peoples R China

来源：

FUZZY SETS AND SYSTEMS | 2023年 / 472卷

基金：

中国国家自然科学基金;

关键词：

Quaternion; Memristive system; Norm; Quasi-synchronization; Nonlinear scalarization; FINITE-TIME SYNCHRONIZATION; STABILITY; DELAYS;

D O I：

10.1016/j.fss.2023.108701

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper, a general class of delayed fuzzy memristive system described by quaternion parameters is considered. By designing a new Lyapunov function and appropriate feedback controller, sufficient conditions formulated by norm inequality are given to ensure the quasi-synchronization of the quaternion-valued fuzzy memristive neural networks. It should be noted that, there is no systematic method to compare the size of two quaternions, so it is difficult to ensure the existence of the closed convex hull. To do so, a nonlinear scalarization approach is proposed in this paper, which established a generalized comparison method. Numerical example is given to show the effectiveness of our new results. (c) 2023 Elsevier B.V. All rights reserved.

引用

页数：15

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