Discarding data to perform more accurate system identification

Presents results concerning the parameter estimates obtained by prediction error methods in the case of system input signals that are insufficiently rich. Such input signals are typical of industrial measurements where occasional stepwise reference changes occur. Using singular value decomposition techniques, the authors propose a new data selection criterion that discards the poorly informative data in order to decrease the total mean square error (MSE) of the estimated parameters