Asymptotic and Finite-Time Cluster Synchronization of Coupled Fractional-Order Neural Networks With Time Delay

被引:107
|
作者
Liu, Peng [1 ,2 ]
Zeng, Zhigang [3 ,4 ]
Wang, Jun [5 ,6 ]
机构
[1] Zhengzhou Univ Light Ind, Coll Elect & Informat Engn, Zhengzhou 450002, Peoples R China
[2] Zhengzhou Univ Light Ind, Henan Key Lab Informat Based Elect Appliances, Zhengzhou 450002, Peoples R China
[3] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan 430074, Peoples R China
[4] Huazhong Univ Sci & Technol, Key Lab Image Proc & Intelligent Control, Educ Minist China, Wuhan 430074, Peoples R China
[5] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China
[6] City Univ Hong Kong, Sch Data Sci, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Synchronization; Neural networks; Complex networks; Delays; Calculus; Delay effects; Mathematical model; Filippov solution; finite-time cluster synchronization; fractional-order neural networks; GLOBAL EXPONENTIAL SYNCHRONIZATION; COMPLEX DYNAMICAL NETWORKS; VARIABLE CHAOTIC SYSTEMS; UNKNOWN-PARAMETERS; STABILITY; CALCULUS;
D O I
10.1109/TNNLS.2019.2962006
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article is devoted to the cluster synchronization issue of coupled fractional-order neural networks. By introducing the stability theory of fractional-order differential systems and the framework of Filippov regularization, some sufficient conditions are derived for ascertaining the asymptotic and finite-time cluster synchronization of coupled fractional-order neural networks, respectively. In addition, the upper bound of the settling time for finite-time cluster synchronization is estimated. Compared with the existing works, the results herein are applicable for fractional-order systems, which could be regarded as an extension of integer-order ones. A numerical example with different cases is presented to illustrate the validity of theoretical results.
引用
收藏
页码:4956 / 4967
页数:12
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