Finite-time projective synchronization of memristor-based delay fractional-order neural networks

被引：84
|
作者：
Zheng, Mingwen [1 ,2 ]
Li, Lixiang [4 ]
Peng, Haipeng [4 ]
Xiao, Jinghua [1 ,3 ]
Yang, Yixian [4 ]
Zhao, Hui [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Sch Sci, Beijing 100876, Peoples R China
[2] Shandong Univ Technol, Sch Sci, Zibo 255000, Peoples R China
[3] Beijing Univ Posts & Telecommun, State Key Lab Informat Photon & Opt Commun, Beijing 100876, Peoples R China
[4] Beijing Univ Posts & Telecommun, Informat Secur Ctr, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China
来源：
NONLINEAR DYNAMICS | 2017年 / 89卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Finite-time projective synchronization; MDFNNs; Linear feedback controller; Volterraintegral equation; ANOMALOUS DIFFUSION; STABILITY; CALCULUS;
D O I：
10.1007/s11071-017-3613-z
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
This paper mainly investigates the finite-time projective synchronization problem of memristor-based delay fractional-order neural networks (MDFNNs). By using the definition of finite-time projective synchronization, combined with the memristor model, set-valued map and differential inclusion theory, Gronwall-Bellman integral inequality and Volterra-integral equation, the finite-time projective of MDFNNs is achieved via the linear feedback controller. Novel sufficient conditions are obtained to guarantee the finite-time projective synchronization of the drive-response MDFNNs. Besides, we also analyze the feasible region of the settling time. Finally, two numerical examples are given to show the effectiveness of the proposed results.
引用
收藏
页码：2641 / 2655
页数：15
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