Exponential stability of Cohen-Grossberg neural networks with delays and impulses

被引：0
|
作者：
Tang, Qing [1 ]
Liu, Anping [1 ]
Li, Huijuan [2 ]
Zou, Min [2 ]
机构：
[1] China Univ Geosci, Sch Math & Phys, Wuhan 430074, Peoples R China
[2] China Univ Geosci, State Key Lab Geol Proc & Mineral Resources, Beijing, Peoples R China
来源：
2009 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, VOL II, PROCEEDINGS | 2009年
基金：
中国国家自然科学基金;
关键词：
FUNCTIONAL-DIFFERENTIAL EQUATIONS; TIME-VARYING DELAYS; ASYMPTOTIC STABILITY;
D O I：
10.1109/AICI.2009.379
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
As an important tool to study practical problems of biology, engineering and image processing, the neural networks has caused more and more attention. Some interesting results on the stability have been obtained. In this paper, the exponential stability of the equilibrium point of a group of Cohen-Grossberg neural networks is obtained by using Lyapunov method and Razumikhin technique.
引用
收藏
页码：535 / +
页数：2
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