Triple-integral method for the stability analysis of delayed neural networks
This paper addresses the stability problem of a delayed neural networks. Combined with the property of convex function, by generalizing the famous Jensen integral inequality, a new triple-integral Lyapunov function is constructed, and a new improved delay-dependent stability criterion is derived. Two numerical examples are presented to illustrate the less conservatism and the effectiveness of the main results.
triple-integral method delayed neural networks jensen integral inequality convex funcation asymptotic stability