Data prefiltering is often used in linear system identification to increase model accuracy in a specified frequency band, as prefiltering 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 note, the role of data and error prefiltering in nonlinear system identification is analyzed and a frequency domain interpretation is provided, based on the Volterra series representation of nonlinear systems. Simulation results illustrate the conclusions of the analysis.

On the role of prefiltering in nonlinear system identification

SPINELLI, WILLIAM;PIRODDI, LUIGI;LOVERA, MARCO
2005-01-01

Abstract

Data prefiltering is often used in linear system identification to increase model accuracy in a specified frequency band, as prefiltering 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 note, the role of data and error prefiltering in nonlinear system identification is analyzed and a frequency domain interpretation is provided, based on the Volterra series representation of nonlinear systems. Simulation results illustrate the conclusions of the analysis.
2005
AUT
File in questo prodotto:
File Dimensione Formato  
2005 - IEEE TAC - SpinelliPiroddiLovera.pdf

Accesso riservato

: Post-Print (DRAFT o Author’s Accepted Manuscript-AAM)
Dimensione 292.63 kB
Formato Adobe PDF
292.63 kB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/554626
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 26
  • ???jsp.display-item.citation.isi??? 18
social impact