Synchronization analysis of fractional delayed memristive neural networks via event-based hybrid impulsive controllers

In this paper, the asymptotic synchronization of Riemann–Liouville fractional delayed memristive neural networks is explored. Firstly, in order to achieve the control target more effectively and economically, a new type of event-based hybrid impulsive controller is designed. In addition, through inequality techniques and impulse analysis methods, some sufficient criteria for asymptotic synchronization are obtained by constructing new Lyapunov–Krasovskii functionals. At the same time, it is verified that Zeno behavior could be eliminated under the given trigger conditions in the error system. It should be noted that some results based on algebraic inequalities fill in the gaps of existing ones and our controller is more practical and energy-saving. Lastly, a simulation instance is depicted to verify the validity and correctness of the submitted conclusions.