Anti-Synchronization Control for Memristor-Based Recurrent Neural Networks

被引：2
|
作者：
Li, Ning [1 ]
Cao, Jinde [1 ,2 ]
Zhou, Mengzhe [1 ]
机构：
[1] Southeast Univ, Res Ctr Complex Syst & Network Sci, Dept Math, Nanjing 210096, Jiangsu, Peoples R China
[2] King Abdulaziz Univ, Fac Sci, Dept Math, Jeddah 21589, Saudi Arabia
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2014 | 2014年 / 8866卷
关键词：
Memristor-based neural networks; Time delay; Feedback control; Anti-Synchronization; TIME-VARYING DELAYS; EXPONENTIAL SYNCHRONIZATION; STABILITY; SYSTEMS; ELEMENT;
D O I：
10.1007/978-3-319-12436-0_4
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we consider the simplified memristor-based neural networks with time-varying delay, under the framework of Filippov's solution and differential inclusion theory, by structuring novel Lyapunov functional and employing feedback control technique, adopting feedback controller, anti-synchronization criteria for memristor-based neural networks with time-varying delay are derived, which depend on the jumps parameter T-i, hence the proposed criteria are more general than existing reference. Finally, an example is provided to show the effectiveness of theoretical result.
引用
收藏
页码：27 / 34
页数：8
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