Advances in Difference Equations
Volume 2007 (2007), Article ID 78160, 18 pages
doi:10.1155/2007/78160
Exponential stability for impulsive BAM neural networks with time-varying delays and reaction-diffusion terms
Qiankun Song1
and Jinde Cao2
1Department of Mathematics, Chongqing Jiaotong University,
ewline Chongqing 400074, China
2Department of Mathematics, Southeast University, Nanjing 210096, China
Abstract
Impulsive bidirectional associative memory neural network model with time-varying delays and reaction-diffusion terms is considered. Several sufficient conditions ensuring the existence, uniqueness, and global exponential stability of equilibrium point for the addressed neural network are derived by M-matrix theory, analytic methods, and inequality techniques. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. The obtained results in this paper are less restrictive than previously known criteria. Two examples are given to show the effectiveness of the obtained results.