Mean-square stability of stochastic quaternion-valued neural networks with variable coefficients and neutral delays

被引:18
|
作者
Song, Qiankun [1 ]
Zeng, Runtian [1 ]
Zhao, Zhenjiang [2 ]
Liu, Yurong [3 ,4 ]
Alsaadi, Fuad E. [5 ]
机构
[1] Chongqing Jiaotong Univ, Dept Math, Chongqing 400074, Peoples R China
[2] Huzhou Univ, Dept Math, Huzhou 313000, Peoples R China
[3] Yangzhou Univ, Dept Math, Yangzhou 225002, Jiangsu, Peoples R China
[4] Yancheng Inst Technol, Sch Math & Phys, Yancheng 224051, Peoples R China
[5] King Abdulaziz Univ, Fac Engn, Dept Elect & Comp Engn, Commun Syst & Networks CSN Res Grp, Jeddah 21589, Saudi Arabia
基金
中国国家自然科学基金;
关键词
Stochastic quaternion-valued neural; networks; Variable coefficients; Neutral delays; Mean-square stability; EXPONENTIAL STABILITY; GLOBAL STABILITY;
D O I
10.1016/j.neucom.2021.11.033
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, the stochastic quaternion-valued neural networks model with variable coefficients and neutral delays is considered, and the mean-square stability criterion is provided via the method of mathematical analysis. In deriving stability criterion, the considered stochastic quaternion-valued neural networks model is implemented as an entirety form without separating the model into two complex-valued or four real-valued models. And the obtained result is valid for stochastic real-valued and complex valued neural networks. A numerical simulation example is given to show the effectiveness of the obtained result. (c) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码:130 / 138
页数:9
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