Improved criteria of delay-dependent stability for discrete-time neural networks with leakage delay

This paper is concerned with the stability analysis of discrete-time neural networks with leakage and time-varying delays. By a novel summation inequality, the technique of reciprocally convex combination and triple Lyapunov-Krasovskii terms, the various cases of time-delay are discussed in detail and improved criteria are established to ensure the delay-dependent stability of discrete-time neural networks. Finally, three examples are given to verify the effectiveness of the proposed methods.