Stability in impulsive Cohen-Grossberg-type BAM neural networks with time-varying delays: A general analysis
In this paper, we investigate a class of impulsive Cohen-Grossberg-type BAM neural networks with time-varying delays. By establishing the delay differential inequality with impulsive initial conditions, and employing the homeomorphism theory, the M-matrix theory and the inequality a Pi(1)(k=1) b(k)(qk)  = 0, b(k) >= 0, q(k) >= 0 with Sigma(1)(k=1)qk=r-1, and r >= 1) some new sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive Cohen-Grossberg-type BAM neural networks with time-varying delays are derived. In particular, the estimate of the exponential convergence rate which depends on the system parameters and the impulsive disturbance intension is also provided. An example is given to show the effectiveness of the results obtained here. (C) 2010 IMACS. Published by Elsevier B.V. All rights reserved.
impulses time-varying delays global exponential stability bi-directional associative memory cohen-grossberg neural networks