Positivity and Stability of Cohen-Grossberg-Type Memristor Neural Networks With Unbounded Delays

This article shows a focus on the positivity and stability of Cohen-Grossberg-type time-delay memristor neural networks. We start by providing the existence and unique theorem of solutions for time-delay memristor neural networks to the case of unbounded delays. It is clear to find that the discriminate criterion of the existence and uniqueness of solutions about the argumented system with unbounded delays plays an important role in other related unbounded time-delay systems. Leveraging the Lyapunov method along with memristor nonlinearity, sufficient and necessary conditions for positivity and stability of Cohen-Grossberg-type memristor neural networks under unbounded delays are gained. Our proposed criteria don’t need any strictly restrictive conditions. These theoretical results derived here will be helpful to understand the convergence performance of memristor electrical systems.