Synchronization of Memristor-Based Coupled Neural Networks with Delay via Intermittent Coupling
Jiejie Chen, Boshan Chen, Zhigang Zeng · 2020
A very broad class of intermittent coupling control is exploited, in which the coupling matrix doesn't have to be Laplacian, its off-diagonal elements can be arbitrary, and the sum of its rows doesn't have to be zero. The synchronization problem of memristor-based coupled neural networks is discussed by using above intermittent coupling control, some simple and applicable criteria on quasi-synchronization and synchronization are obtained. In particular, the activation functions need not be bounded in the obtained results. In addition, a numerical example is provided to test the results in theory analysis.