Finite-time Sp-almost periodic synchronization of fractional-order octonion-valued Hopfield neural networks

被引:6
|
作者
Huo, Nina [1 ]
Li, Yongkun [2 ]
机构
[1] Hefei Univ, Key Lab Appl Math & Mech Artificial Intelligence, Hefei 230601, Anhui, Peoples R China
[2] Yunnan Univ, Dept Math, Kunming 650091, Yunnan, Peoples R China
基金
中国国家自然科学基金;
关键词
Octonion-valued Hopfield neural network; Sp-almost periodic solution; Finite-time synchronization; STABILITY;
D O I
10.1016/j.chaos.2023.113721
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In this paper, we consider a fractional-order octonion-valued Hopfield neural network. Based on the fixed point theorem and analytical technique, we first establish the existence and uniqueness of Sp-almost periodic solutions of the network by direct method. Then, we take the fractional-order octonion-valued Hopfield neural network as the driving system and introduce the corresponding response system to study their finite-time synchronization. Finally, we use an example to illustrate the validity of our results. Even when the neural network under consideration degenerates into real-valued one, our results are completely new.
引用
收藏
页数:10
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