Adaptive finite-time cluster synchronization of neutral-type coupled neural networks with mixed delays

被引：26
作者：
He, Juan-Juan [1 ,2 ]
Lin, Ya-Qi [1 ,2 ]
Ge, Ming-Feng [3 ]
Liang, Chang-Duo [3 ]
Ding, Teng-Fei [3 ]
Wang, Leimin [4 ]
机构：
[1] Wuhan Univ Sci & Technol, Coll Comp Sci & Technol, Wuhan 430081, Peoples R China
[2] Hubei Prov Key Lab Intelligent Informat Proc & Re, Wuhan 430081, Peoples R China
[3] China Univ Geosci, Sch Mech Engn & Elect Informat, Wuhan 430074, Peoples R China
[4] China Univ Geosci, Sch Automat, Wuhan 430074, Peoples R China
来源：
NEUROCOMPUTING | 2020年 / 384卷
基金：
中国国家自然科学基金;
关键词：
Neutral-type coupled neural networks (NCNNs); Finite-time cluster synchronization; Adaptive control; Mixed delays; COMPLEX DYNAMICAL NETWORKS; VARYING DELAYS; ANTI-SYNCHRONIZATION; STATE ESTIMATION; CONSENSUS; SYSTEMS; DISCRETE; COMMUNICATION; TRACKING; NODES;
D O I：
10.1016/j.neucom.2019.11.046
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 investigates the adaptive finite-time cluster synchronization problem of the neutral-type coupled neural networks (NCNNs) with mixed delays. Compared with the traditional neural networks, the model of NCNNs is more general in some sense, due to that it involves state delays, distributed delays and coupling delays. In this paper, a novel, adaptive and closed-loop control control algorithm is proposed to achieve the finite-time cluster synchronization of NCNNs with mixed delays. In addition, the sufficient conditions on the control parameters for stabilizing the closed-loop system are derived by leveraging the Lyapunov stability argument. Finally, the simulation results are carried out to illustrate the validity and feasibility of the proposed algorithm. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码：11 / 20
页数：10
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