Robust stabilization of uncertain neural networks with additive time-varying delays∗

This study is mainly concerned with the problem of robust stabilization of neural networks with two additive time-varying delays via Wirtinger-based double integral inequality. The main purpose of this paper is to design a memoryless state feedback controller which ensuring that the global asymptotic stability of closed loop system. By constructing a suitable Lyapunov-Krosovskii functionals, utilizing Wirtinger-based double integral inequality, the sufficient criteria are derived in terms of linear matrix inequalities technique which ensuring the global asymptotic stability of the proposed neural networks with norm bounded uncertainties. The desired controllers can be calculated by solving the linear matrix inequalities with the help of some standard numerical packages. Finally, the numerical examples are given to demonstrate the effectiveness of the theoretical results.