Further Results on Fixed-Time Cluster Synchronization of Coupled Neural Networks

被引：3
|
作者：
Huang, Rujia [1 ]
Liu, Xiaoyang [1 ,2 ]
Cao, Jinde [3 ]
机构：
[1] Jiangsu Normal Univ, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China
[2] Minist Educ, Key Lab Syst Control & Informat Proc, Shanghai 200240, Jiangsu, Peoples R China
[3] Southeast Univ, Sch Math, Nanjing 210096, Jiangsu, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 2023年 / 55卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Cluster synchronization; Coupled neural networks; External disturbances; Fixed-time synchronization; COMPLEX DYNAMICAL NETWORKS; FINITE-TIME; STABILITY; FRAMEWORK;
D O I：
10.1007/s11063-022-11081-4
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper considers the fixed-time cluster synchronization of nonlinear coupled neural networks. Some novel cost-saving fixed-time controllers are developed to ensure the cluster synchronization for the coupled neural networks with/without disturbances. Different from the traditional fixed-time synchronization controllers containing many nonlinear terms, the newly designed control protocol only holds one power-exponent term. Two numerical examples are provided to illustrate the feasibility of the derived results.
引用
收藏
页码：5069 / 5085
页数：17
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