Robust stability analysis of generalized neural networks with multiple discrete delays and multiple distributed delays

Abstract

Using the Lyapunov–Krasovskii functional method and the linear matrix inequality (LMI) technique, this paper is concerned with the robust stability of generalized neural networks with multiple discrete delays and multiple distributed delays. The global stability of the equilibrium point is proved under mild conditions, where the activation function is neither differentiable nor strictly monotone. For the considered system, a novel robust stability criterion of the system is derived, which can be easily solved by efficient convex optimization algorithms. And two numerical examples are given to justify the obtained results.