| Popis: |
Data pre-filtering is often used in linear identification to increase model accuracy in a specified frequency band, as pre-filtering is equivalent to a frequency weighting on the prediction error function. However, this interpretation applies only to a strictly linear setting of the identification problem. In this paper, the role of data and error pre-filtering in nonlinear system identification is analyzed and a frequency domain interpretation is provided, based on the use of Volterra series representations for the true system and the considered model structure. Simulation results illustrate the conclusions of the analysis. |
