A new identification method based on feed forward networks is presented for nonlinear time varying systems. We apply local extended Kalman Algorithm to train feed forward networks, this algorithm needs no matrix inversion computation and has the higher convergence speed and the smaller storage required in comparison to the global extended Kalman Algorithm. Simulation results show the present method has better effect on nonlinear time varying systems identification.