DocumentCode
876620
Title
Robust global exponential stability of Cohen-Grossberg neural networks with time delays
Author
Chen, Tianping ; Rong, Libin
Author_Institution
Inst. of Math., Fudan Univ., Shanghai, China
Volume
15
Issue
1
fYear
2004
Firstpage
203
Lastpage
206
Abstract
The authors discuss delayed Cohen-Grossberg neural network models and investigate their global exponential stability of the equilibrium point for the systems. A set of sufficient conditions ensuring robust global exponential convergence of the Cohen-Grossberg neural networks with time delays are given.
Keywords
asymptotic stability; delays; neural nets; Cohen-Grossberg neural networks; M-matrix; equilibrium point; global exponential convergence; global exponential stability; robust global exponential convergence; robust global exponential stability; sufficient conditions; time delays; Convergence; Delay effects; Delay systems; Hopfield neural networks; Image converters; Neural networks; Neurons; Robust stability; Robustness; Sufficient conditions; Neural Networks (Computer); Time Factors;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/TNN.2003.822974
Filename
1263592
Link To Document