Exponential Stability and Sampled-Data Synchronization of Delayed Complex-Valued Memristive Neural Networks

摘要

This paper is devoted to the global exponential stability (GES) and synchronization control of delayed complex-valued memristive neural networks (CVMNNs). The criterion on the existence, uniqueness and GES of the equilibrium point (EP) for delayed CVMNNs is established by constructing a suitable Lyapunov functional and using the homeomorphism theory as well as linear matrix inequality. Meanwhile, a sampled-data controller is designed to synchronize the master and slave systems under the framework of inequality techniques and Lyapunov method. Finally, two examples are presented to show the validity of the obtained results.