Generalized Function Projective Lag Synchronization between Two Different Neural Networks

摘要

The generalized function projective lag synchronization (GFPLS) is proposed in this paper. The scaling functions which we have investigated are not only depending on time, but also depending on the networks. Based on Lyapunov stability theory, a feedback controller and several sufficient conditions are designed such that the response networks can realize lag-synchronize with the drive networks. Finally, the corresponding numerical simulations are performed to demonstrate the validity of the presented synchronization method.