Global exponential stability of periodic solution for delayed complex-valued neural networks with impulses

In this paper, a class of delayed complex-valued neural networks with impulses is investigated. By using Mawhin׳s continuation theorem of coincidence degree theory, a series of useful criteria on existence of periodic solution are established for the complex-valued neural networks. By constructing appropriate Lyapunov–Krasovskii functional, some sufficient conditions are derived for the global exponential stability of periodic solutions to the complex-valued neural networks. Finally, several examples with numerical simulations are given to highlight the effectiveness of our theoretical results via standard numerical software.