Finite-time stability analysis of fractional-order neural networks with delay

被引：141
|
作者：
Yang, Xujun [1 ]
Song, Qiankun [1 ]
Liu, Yurong [2 ,3 ]
Zhao, Zhenjiang [4 ]
机构：
[1] Chongqing Jiaotong Univ, Sch Management, Chongqing 400074, Peoples R China
[2] Yangzhou Univ, Dept Math, Yangzhou 225002, Jiangsu, Peoples R China
[3] King Abdulaziz Univ, Fac Engn, Commun Syst & Networks CSN Res Grp, Jeddah 21589, Saudi Arabia
[4] Huzhou Teachers Coll, Dept Math, Huzhou 313000, Peoples R China
来源：
NEUROCOMPUTING | 2015年 / 152卷
基金：
中国国家自然科学基金;
关键词：
Fractional order neural networks; Equilibrium point; Existence; Uniqueness; Finite-time stability; GLOBAL EXPONENTIAL STABILITY; NONLINEAR-SYSTEMS; STABILIZATION; DYNAMICS;
D O I：
10.1016/j.neucom.2014.11.023
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Stability analysis of fractional-order neural networks with delay is addressed in this paper. By using the contracting mapping principle, method of iteration and inequality techniques, a sufficient condition is established to ensure the existence, uniqueness and finite-time stability of the equilibrium point of the proposed networks. Finally, based on the Predictor-Corrector Approach, two numerical examples are presented to illustrate the validity and feasibility of the obtained result. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码：19 / 26
页数：8
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