State Estimation of Fractional-Order Neural Networks with Time Delay

被引：0
|
作者：
Bao, Haibo [1 ]
Cao, Jinde [2 ]
机构：
[1] Southwest Univ, Sch Math & Stat, Chongqing 400715, Peoples R China
[2] Southeast Univ, Sch Math, Nanjing 210096, Jiangsu, Peoples R China
来源：
2017 CHINESE AUTOMATION CONGRESS (CAC) | 2017年
基金：
中国国家自然科学基金;
关键词：
Fractional-order; state estimation; linear matrix inequality (LMI); neural networks;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper investigates the state estimation of fractional-order neural networks (FNNs) with time delay. This is the first to study the state estimation for delayed fractional-order nonlinear system. According to fractional-order Lyapunov direct approach together with linear matrix inequalities (LMIs), sufficient criteria are given to ensure the asymptotical stability of the estimation error system. At last, numerical simulations are exploited to show the validity of the obtained resutls.
引用
收藏
页码：1573 / 1577
页数：5
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