Synchronization of fractional complex-valued neural networks with pantograph delays and inhibitory factors

被引：2
作者：
Xu, Yao [1 ]
Wang, Haodong [1 ]
Yu, Jintong [2 ]
Li, Wenxue [1 ]
机构：
[1] Harbin Inst Technol Weihai, Dept Math, Weihai 264209, Peoples R China
[2] Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Shanghai 200240, Peoples R China
来源：
NEUROCOMPUTING | 2023年 / 559卷
关键词：
Pantograph delays; Fractional complex-valued neural networks; Inhibitory factors; Synchronization; FINITE-TIME; UNCERTAIN PARAMETERS; STABILITY; STABILIZATION; CRITERIA;
D O I：
10.1016/j.neucom.2023.126797
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 global synchronization of fractional complex-valued neural networks with pantograph delays and inhibitory factors is investigated, and some sufficient conditions are obtained. It deserves to mention that the attained sufficient conditions show that some factors including the pantograph coefficient, coupling connection weights, inhibitory factors, and the order of fractional derivative have an influence on network synchronization. Moreover, when complex-valued neural networks degenerate into real-valued cases and inhibitory factors are not taken into consideration, they are also discussed, and two corollaries are derived. Finally, to validate the feasibility of the theoretical results, a numerical example is presented. Meanwhile, some contrastive numerical results are given to illustrate the relationships among network synchronization, pantograph coefficient, and inhibitory factors.
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页数：10
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