Global Synchronization of Fractional-Order Multi-Delay Coupled Neural Networks with Multi-Link Complicated Structures via Hybrid Impulsive Control

被引:7
|
作者
Fan, Hongguang [1 ,2 ,3 ]
Rao, Yue [1 ]
Shi, Kaibo [4 ]
Wen, Hui [2 ,5 ]
机构
[1] Chengdu Univ, Coll Comp, Chengdu 610106, Peoples R China
[2] Fujian Prov Univ, Engn Res Ctr Big Data Applicat Private Hlth Med, Putian 351100, Peoples R China
[3] Hunan Univ Sci & Technol, Sch Math & Computat Sci, Xiangtan 411201, Peoples R China
[4] Chengdu Univ, Sch Elect Informat & Elect Engn, Chengdu 610106, Peoples R China
[5] Putian Univ, New Engn Ind Coll, Putian 351100, Peoples R China
关键词
coupled neural network; synchronization; multi-link structure; impulsive pinning control; PROJECTIVE SYNCHRONIZATION; COMPLEX NETWORKS;
D O I
10.3390/math11143051
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This study discusses the global asymptotical synchronization of fractional-order multi-delay coupled neural networks (FMCNNs) via hybrid control schemes. In addition to internal delays and different coupling delays, more importantly, multi-link complicated structures are introduced into our model. Unlike most existing works, the synchronization target is not the special solution of an isolated node, and a more universally accepted synchronization goal involving the average neuron states is introduced. A generalized multi-delay impulsive comparison principle with fractional order is given to solve the difficulties resulting from different delays and multi-link structures. To reduce control costs, a pinned node strategy based on the principle of statistical sorting is provided, and then a new hybrid impulsive pinning control method is established. Based on fractional-order impulsive inequalities, Laplace transforms, and fractional order stability theory, novel synchronization criteria are derived to guarantee the asymptotical synchronization of the considered FMCNN. The derived theoretical results can effectively extend the existing achievements for fractional-order neural networks with a multi-link nature.
引用
收藏
页数:17
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