Exponential stabilization of neural networks with time-varying delay by periodically intermittent control

This paper investigates the exponential stabilization of neural networks with time-varying delay by periodically intermittent control. By employing the free-matrix-based integral inequality and using some new analysis techniques, some novel exponential stabilization criteria are derived based on the Lyapunov–Krasovskii (L–K) functional method. The obtained criteria are in terms of linear matrix inequalities without transcendental equation, instead of nonlinear matrix inequalities, which reduces the computational burden. Compared to existing results in corresponding literatures, our results have a wider range of applications, and overcome no feasible solution if the information on the sizes of delays is ignored for the design of the intermittent controller. A numerical simulation is provided to show the effectiveness and the benefits of the theoretical results.