New Stability Criterion For Delayed Neural Networks With Impulses

This paper studies the exponential stability of impulsive delayed neural networks (IDNN). By employing the standard Lyapunov function and the modified Halanay inequalities, two new sufficient conditions guaranteeing the global exponential stability of the origin of IDNN are established. The proposed results characterize the effects of impulses, delay and the exponential convergence rate of the impulse-free DNN in an aggregated form.