4.7 Article

Criteria for exponential stability of Cohen-Grossberg neural networks

Journal

NEURAL NETWORKS
Volume 17, Issue 10, Pages 1401-1414

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2004.08.007

Keywords

global exponential stability; Cohen-Grossberg model; neural networks; Lyapunov functionals

Ask authors/readers for more resources

In this paper. the Cohen-Grossberg neural network models without and with time delays are considered. By constructing several novel Lyapunov functionals, some sufficient criteria for the existence of a unique equilibrium and global exponential stability of the network are derived. These results are fairly general and can be easily verified. Besides, the approach of the analysis allows one to consider different types of activation functions, including piecewise linear, sigmoids with bounded activations as well as C-1-smooth sigmoids. In the meantime, our approach does not require any symmetric assumption of the connection matrix. It is believed that these results are significant and useful for the design and applications of the Cohen-Grossberg model. (C) 2004 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available