Finite-time synchronization of memristor-based Cohen-Grossberg neural networks with time-varying delays

This paper concerns the problem of global and local finite-time synchronization for a class of memristor-based Cohen-Grossberg neural networks with time-varying delays by designing an appropriate feedback controller. Through a nonlinear transformation, we derive an alternative system from the considered memristor-based Cohen-Grossberg neural networks. Then, by considering the finite-time synchronization of the alternative system, we obtain some novel and effective finite-time synchronization criteria for the considered memristor-based Cohen-Grossberg neural networks. These results generalize and extend some previous known works on conventional Cohen-Grossberg neural networks. Finally, numerical simulations are given to present the effectiveness of the theoretical results. (C) 2016 Elsevier B.V. All rights reserved.