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… Click to show full abstract
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.
               
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