Stability analysis of delayed neural networks based on a relaxed delay-product-type Lyapunov functional

Abstract

This paper deals with the stability analysis of delayed neural networks. A necessary and sufficient condition for positivity or negativity of the high-order polynomial over a finite interval is derived. An appropriate Lyapunov–Krasovskii functional (LKF), including a relax delay-product-type Lyapunov functional, is constructed. The necessary and sufficient condition of the polynomial inequality and a relaxed delay-product-type Lyapunov functional are employed to derive less conservative stability criteria. Finally, three commonly used numerical examples are presented to demonstrate the effectiveness and less conservativeness of the proposed method.