New stability results for delayed neural networks with data packet dropouts

This paper further investigates the stability analysis of delayed neural networks (DNNs) with data packet dropouts. Firstly, the delay-product-type function method is introduced to construct a suitable Lyapunov–Krasovskii functional (LKF) with delay-dependent matrices, which fully considers the integral terms, non-integral terms and time-delay correlation terms. Then, by applying free-matrix-base inequality (FMBI) and other valid inequalities mathematical analysis techniques, new stability criteria are established. Meanwhile, by solving a set of linear matrix inequalities (LMIs), the corresponding controllers are designed to ensure the system state stabilization. Finally, two examples are given to demonstrate the validity and feasibility of the proposed method.