Robust Finite-Time Synchronization of Recurrent Neural Networks via Saturated Control

This brief studies the finite-time synchronization of a class of recurrent neural networks, where the dual effects of the saturation structure and uncertain factors on the system are fully considered. By designing different classes of saturated controllers, some sufficient conditions guaranteeing robust finite-time synchronization are proposed, where the estimations of the settling-time and the domain of attraction are obtained. In particular, in the framework of saturation structure, the designed controller can be improved a simpler form to further acquire globally robust finite-time synchronization. Finally, a numerical example is demonstrated to verify the presented results.