Finite-Time Stability of Fractional-Order Neural Networks with Delay

被引：107
|
作者：
Wu Ran-Chao [1 ]
Hei Xin-Dong [1 ]
Chen Li-Ping [2 ]
机构：
[1] Anhui Univ, Sch Math, Hefei 230039, Peoples R China
[2] Chongqing Univ, Sch Automat, Chongqing 400044, Peoples R China
来源：
COMMUNICATIONS IN THEORETICAL PHYSICS | 2013年 / 60卷 / 02期
基金：
高等学校博士学科点专项科研基金;
关键词：
neural networks; fractional-order; finite-time stability; Gronwall inequality; DYNAMICS; NEURONS; CHAOS;
D O I：
10.1088/0253-6102/60/2/08
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
Finite-time stability of a class of fractional-order neural networks is investigated in this paper. By Laplace transform, the generalized Gronwall inequality and estimates of Mittag-Leliler functions, sufficient conditions are presented to ensure the finite-time stability of such neural models with the Caputo fractional derivatives. Furthermore, results about asymptotical stability of fractional-order neural models are also obtained.
引用
收藏
页码：189 / 193
页数：5
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