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Global Exponential Stability of Delayed Neural Networks(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2007年02期
Page:
6-10
Research Field:
数学
Publishing date:

Info

Title:
Global Exponential Stability of Delayed Neural Networks
Author(s):
Jiang Qiuhao1; 2; Cao Jinde2
1.Department of Mathematics,China Pharmaceutical University,Nanjing 210009,China
2. Department ofMathematics, Southeast University, Nanjing 210096, China
Keywords:
neural networks;  exponential stability;  time-varying delay
PACS:
O175;O177
DOI:
-
Abstract:
In recent years, the study of cellular neural networks with delay (DCNNs) draws the attention of more and more specialists due to its extensive app lication in the fields of image p rocessing etc. The ear ly results on stability of DCNNs are usually rep resented by the elements ofweightmatrices of the network. In this paper, by emp loying the Lyapunov-Krasovskiimethod, global exponential stability of DCNNs is in vestigated, and sufficient conditions are obtained in the form ofmatrixwith ( semi-positive) positive defi niteness, and they are easier to be checked in p ractice. Compared to the earlier criteria, our results have more extensive app lications.

References:

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Memo

Memo:
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Last Update: 2013-05-05