Robust exponential stability of fractional-order coupled quaternion-valued neural networks with parametric uncertainties and impulsive effects

被引:13
|
作者
Li, Hong-Li [1 ]
Kao, Yonggui [2 ]
Hu, Cheng [1 ]
Jiang, Haijun [1 ]
Jiang, Yao-Lin [3 ]
机构
[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Peoples R China
[2] Harbin Inst Technol Weihai, Dept Math, Weihai 264209, Shandong, Peoples R China
[3] Xi An Jiao Tong Univ, Dept Math, Xian 710049, Peoples R China
基金
中国国家自然科学基金;
关键词
Robust exponential stability; Fractional-order; Coupled quaternion-valued neural networks; Parametric uncertainties; Average impulsive interval; MITTAG-LEFFLER STABILITY; DIFFERENTIAL-EQUATIONS; SYNCHRONIZATION ANALYSIS; TIME SYNCHRONIZATION; LYAPUNOV FUNCTIONS; SYSTEMS; DELAYS;
D O I
10.1016/j.chaos.2020.110598
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper investigates the robust exponential stability (RES) issue for fractional-order coupled quaternion-valued neural networks (FCQNNs) with parametric uncertainties and impulsive effects. According to the rules of quaternion algebra and its properties, a new fractional-order inequality is built, which greatly generalizes the existing fractional-order inequality in the real domain. On the basis of quaternion inequality technique, newly established inequality, together with algebraic graph theory and iterative method, several criteria for easy verification are presented, which depend on not only impulsive gain and maximum impulsive interval but also the scale of the controlled vertices. Furthermore, the convergence rate of the considered FCQNN is also estimated. Finally, numerical results are given to substantiate our theoretical criteria. (c) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:8
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