Fixed-time synchronization of delayed memristor-based recurrent neural networks

被引：282
|
作者：
Cao, Jinde [1 ]
Li, Ruoxia
机构：
[1] Southeast Univ, Sch Math, Nanjing 210096, Jiangsu, Peoples R China
来源：
SCIENCE CHINA-INFORMATION SCIENCES | 2017年 / 60卷 / 03期
基金：
中国国家自然科学基金;
关键词：
memristor; fixed-time synchronization; nonlinear control; master-slave systems; time delays;
D O I：
10.1007/s11432-016-0555-2
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper focuses on the fixed-time synchronization control methodology for a class of delayed memristor-based recurrent neural networks. Based on Lyapunov functionals, analytical techniques, and together with novel control algorithms, sufficient conditions are established to achieve fixed-time synchronization of the master and slave memristive systems. Moreover, the settling time of fixed-time synchronization is estimated, which can be adjusted to desired values regardless of the initial conditions. Finally, the corresponding simulation results are included to show the effectiveness of the proposed methodology derived in this paper.
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页数：15
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