Asymptotic stability of delayed fractional-order neural networks with impulsive effects

被引：96
|
作者：
Wang, Fei [1 ]
Yang, Yongqing [1 ]
Hu, Manfeng [1 ]
机构：
[1] Jiangnan Univ, Sch Sci, Key Lab Adv Proc Control Light Ind, Minist Educ, Wuxi 214122, Peoples R China
来源：
NEUROCOMPUTING | 2015年 / 154卷
基金：
中国国家自然科学基金;
关键词：
Fractional-order; Neural networks; Asymptotic stability; Impulsive; Delay; Riemann-Liouville; DIFFERENTIAL-EQUATIONS; SYNCHRONIZATION; SYSTEMS; CRITERIA;
D O I：
10.1016/j.neucom.2014.11.068
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper has investigated the existence, uniqueness and the global asymptotic stability of equilibrium point for delayed fractional-order neural networks with impulsive effects. A lemma has been given based on Riemann-Liouville operator, which plays an important role in the stability analysis. Some sufficient conditions are derived to ensure the existence, uniqueness and the asymptotic stability of the fractional-order neural networks. An illustrative example is given to show the effectiveness of the obtained results by using a new numerical method of fractional-order differential equations. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码：239 / 244
页数：6
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