Intermittent control of memristor-based recurrent neural networks with time-varying delays

We discuss the design of periodical intermittent controller for a memristor-based neural network (MRNN). By introducing a proper Lyapunov functional, we prove that the equilibrium point of the MRNN is exponentially stable under the periodical intermittent control. In particular, the control period, width, and coefficients in the intermittent controller can be determined by an linear matrix inequality without introducing any parameters outside the MRNNs. Finally, two illustrated experiments are employed to indicate the validity of the obtained results.