Stability analysis of recurrent neural networks with interval time-varying delay via free-matrix-based integral inequality

This paper is concerned with the stability analysis of recurrent neural networks with an interval time-varying delay. A new Lyapunov–Krasovskii functional (LKF) containing some augmented double integral and triple integral terms is constructed, in which the information of the activation function and the lower bound of the delay are both fully considered. Then, a free-matrix-based integral inequality is employed to deal with the derivative of the LKF such that an improved stability criterion is derived. Finally, two numerical examples are provided to illustrate the effectiveness and the benefit of the proposed stability criterion.