Aperiodically Intermittent Control Strategy and Adaptive Synchronization of Neural Networks With Inertial and Memristive Terms

The problem of adaptive aperiodic intermittent synchronization scheme is studied for inertial memristive delayed neural networks by using a piecewise Lyapunov function in this article. First, an appropriate two-parameter variable replace technique is proposed about the second-order differential equation, and inertial memristive delayed neural systems can be replaced by first-order derivatives of states. Second, an aperiodic intermittent control strategy which can be degenerated periodically intermittent controller or continue feedback controller is designed. Third, by building a piecewise Lyapunov function and using piecewise analytical skills, a number of novel and effective norms to guarantee the exponential synchronization and global exponential synchronization of memristive delayed inertial systems are obtained. Besides, an adaptive control method is proposed to adjust control gains. And asymptotic synchronization and exponential synchronization are ensured by constructing of Lyapunov functional. In the end, simulation results are given to support the significance of the research work.