Novel extended dissipativity criteria for generalized neural networks with interval discrete and distributed time-varying delays

Abstract The problem of asymptotic stability and extended dissipativity analysis for the generalized neural networks with interval discrete distributed time-varying delays is investigated. Based on a suitable Lyapunov–Krasovskii functional (LKF), an improved Wirtinger single integral inequality, novel triple convex combination technique, new criteria are achieved delays. By above methods, less conservative obtained special case networks. using Matlab LMI toolbox, derived expressed in terms linear matrix inequalities (LMIs) that cover $H_{\infty }$ H ∞ , $L_{2}$ L 2 – $L_{\infty passivity, performance by setting parameters general index. Finally, we show numerical examples which than other literature. Moreover, present networks, including