Global Mittag-Leffler stability and synchronization of memristor-based fractional-order neural networks

被引：483
|
作者：
Chen, Jiejie
Zeng, Zhigang [1 ]
Jiang, Ping
机构：
[1] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Peoples R China
来源：
NEURAL NETWORKS | 2014年 / 51卷
关键词：
Fractional-order; Memristor-based neural networks; Global Mittag-Leffler stability; Synchronization; Filippov's solution; TIME-VARYING DELAYS; CHAOS; CALCULUS; MODEL; ELEMENT; FLUID;
D O I：
10.1016/j.neunet.2013.11.016
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The present paper introduces memristor-based fractional-order neural networks. The conditions on the global Mittag-Leffler stability and synchronization are established by using Lyapunov method for these networks. The analysis in the paper employs results from the theory of fractional-order differential equations with discontinuous right-hand sides. The obtained results extend and improve some previous works on conventional memristor-based recurrent neural networks. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.
引用
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页码：1 / 8
页数：8
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