The paper concentrates on the input-to-state stability of memristor-based complex-valued neural networks with time delays. Several new stability criteria are proposed by utilizing the Lyapunov function, differential inclusions theory and set-valued maps. The obtained results generalize some existing literature about real-valued neural networks as special conditions.