Exponential Synchronization of Stochastic Memristive Neural Networks with Delays Using Periodically Intermittent Observation Feedback Control

This paper focuses on the mean-square exponential synchronization problem for the stochastic memristive neural networks with delays through periodic intermittent observation feedback control (PIOFC). The goal of this issue is to design a discrete observation controller that tolerates the stochastic perturbation. By constructing a Lyapunov function, we establish a sufficient condition to guarantee the mean-square synchronization of the networks. In addition, some criteria are applied to ensure that the drive system can be synchronized to the response system. Finally, some simulation examples are raised to demonstrate the effectiveness of our proposed scheme.