Weighted Sum Synchronization of Stochastic Delayed Memristive Neural Networks via a Novel Hybrid Control

Abstract

This paper investigates the weighted sum synchronization issue of stochastic delayed memristive neural networks (SDMNNs) via a novel hybrid control (HC). The switching strategy is applied to the controller to cope with the challenges induced concurrently by impulses, stochastic turbulence and time-varying delays. Furthermore, the control costs can be reduced by using this designed controller. Finally, novel Lyapunov functions and new analytical methods are contructed, whic can be used to realize the weighted sum synchronization of SDMNNs via HC.