The application research on system identification of Jordan networks

A new kind of training method of Jordan neural network is given, which is based on strongtracking filter. The Jordan network is able to express the dynamic characteristic, theimproved network can also reflect state characteristic, and is suitable to dynamic systemidentification. Strong tracking filter has the strongpoint of the robustness is better and theconvergence is quick, and when they are integrated, the better identification effect is gained.At last, a model identification example is given to show the effectiveness of the method.