Impulsive effect on global exponential stability of BAM fuzzy cellular neural networks with time-varying delays

Abstract

In this article, a class of impulsive bidirectional associative memory (BAM) fuzzy cellular neural networks (FCNNs) with time-varying delays is formulated and investigated. By employing delay differential inequality and M-matrix theory, some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive BAM FCNNs with time-varying delays are obtained. In particular, a precise estimate of the exponential convergence rate is also provided, which depends on system parameters and impulsive perturbation intention. It is believed that these results are significant and useful for the design and applications of BAM FCNNs. An example is given to show the effectiveness of the results obtained here.

Keywords:

• bidirectional associative memory
• fuzzy cellular neural networks
• time-varying delays
• global exponential stability
• impulses

AMS Subject Classifications::

• 92B20
• 34K20

Acknowledgement

This work is supported by the open fund of Artificial Intelligence of key Laboratory of Sichuan Province Under Grant 2008RK003.