Novel robust stability criteria for interval Cohen-Grossberg neural networks with time-varying delays

Authors:
Xiaolin Li
Affiliations:
Department of Mathematics, University of Shanghai, Shangda Road, 200444 Shanghai, China
Venue:
International Journal of Systems, Control and Communications
Year:
2010

Citing 2
Cited 0

Criteria for exponential stability of Cohen-Grossberg neural networks

Neural Networks
Robust global exponential stability of Cohen-Grossberg neural networks with time delays

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a new sufficient criterion is derived for the uniqueness and global robust stability of the equilibrium point for interval Cohen-Grossberg neural networks with time-varying delays. A new inequality technique combined with the Lyapunov functional method and Linear Matrix Inequality (LMI) technique is taken to investigate this problem. The result is computationally efficient, since it is in the form of a LMI. Two examples are also provided to illustrate the effectiveness of our result.