Global Exponential Synchronization of Delayed BAM Neural Networks

Abstract

In order to enhance the presented synchronization scheme level, this paper deals with the synchronization problem of a class of bidirectional associative memory (BAM) neural networks with delays. Using the drive-response concept, a feedback control law is derived to achieve the state synchronization of two identical BAM neural networks. Moreover, based on the Lyapunov stability method and the Halanay inequality lemma, two delay-independent sufficient exponential synchronization conditions are derived. The results in the present study provide new insights into the exponential synchronization of BAM neural networks. An example is given to show the effectiveness of the obtained results.

Global exponential stabilization of delayed BAM neural networks: a matrix measure approach

“…Then, the analysis of the delayed BAM neural networks has received considerable attention; especially, dynamical behaviors of delayed BAM neural networks have been extensively investigated. It can be noticed that most of the existing works focus on the stability analysis [3,4], synchronization problem [5], periodic oscillation [6,7], optional problem [8,9], or bifurcation [10,11]. In [3], a new robust stability was studied for a class of uncertain neutraltype neural networks with discrete and distributed delays.…”

“…In [3], a new robust stability was studied for a class of uncertain neutraltype neural networks with discrete and distributed delays. In [5], global exponential synchronization of delayed BAM neural networks was investigated by using Lyapunov stability theory and Halanay inequality. In [7], the existence of periodic solutions in a six-neuron BAM network model by means of Chafee's criterion of limit cycle was discussed.…”