Exponential stability criterion for neural networks with time-varying delay

This paper focuses on the problem of exponential stability for neural networks with time-varying delay. By introducing a novel Lyapunov-Krasovskii functional, a new criterion of exponential stability is derived. This newly presented criterion does not require all the symmetric matrices involved in the employed integral terms of the quadratic Lyapunov-Krasovskii functional to be positive definite. The obtained criterion proves to be truly less conservative than some of the most recent results. Finally, two numerical examples are provided to verify the effectiveness and benefit of the presented criterion.