Finite-time Synchronization of the Neural Networks with Nodes of Different Dimensions

The finite-time synchronization of the neural networks with nodes of different dimensions is investigated in this study. The drive system and response system are the coupling networks of different dimensions, indicating that the node numbers of each single network in these systems are not the same. The nonlinear feedback controller is designed for such dynamic neural networks. The sufficient conditions of finite-time synchronization of the dynamic neural networks are derived on the basis of Lyapunov stability theory. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method.