Dynamical analysis of memristor-based fractional-order neural networks with time delay

被引：12
|
作者：
Cui, Xueli [1 ]
Yu, Yongguang [1 ]
Wang, Hu [2 ]
Hu, Wei [1 ]
机构：
[1] Beijing Jiaotong Univ, Dept Math, Beijing 100044, Peoples R China
[2] Cent Univ Finance & Econ, Sch Math & Stat, Beijing 100081, Peoples R China
来源：
MODERN PHYSICS LETTERS B | 2016年 / 30卷 / 18期
关键词：
Neural networks; fractional-order; memristor; time delay; GLOBAL EXPONENTIAL STABILITY; VARYING DELAYS;
D O I：
10.1142/S0217984916502717
中图分类号：
O59 [应用物理学];
学科分类号：
摘要：
In this paper, the memristor-based fractional-order neural networks with time delay are analyzed. Based on the theories of set-value maps, differential inclusions and Filippov's solution, some sufficient conditions for asymptotic stability of this neural network model are obtained when the external inputs are constants. Besides, uniform stability condition is derived when the external inputs are time-varying, and its attractive interval is estimated. Finally, numerical examples are given to verify our results.
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页数：21
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