This work deals with the identification of errors-in-variables models corrupted by white and uncorrelated gaussian noises. By introducing an auxiliary process, it is possible to obtain a maximum likelihood solution of this identification problem, by means of a two-step iterative algorithm. This approach allows also to estimate, as a byproduct, the noise-free input and output sequences. Moreover, an analytic expression of the finite Cramer-Rao lower bound is derived. The method does not require any particular assumption on the input process, however the ratio of the noise variances is assumed as known. The effectiveness of the proposed algorithm has been verified by means of Monte Carlo simulations.

R. Diversi, R. Guidorzi, U. Soverini (2007). Maximum likelihood identification of noisy input-output models. AUTOMATICA, 43, 464-472 [10.1016/j.automatica.2006.09.009].

Maximum likelihood identification of noisy input-output models

DIVERSI, ROBERTO;GUIDORZI, ROBERTO;SOVERINI, UMBERTO
2007

Abstract

This work deals with the identification of errors-in-variables models corrupted by white and uncorrelated gaussian noises. By introducing an auxiliary process, it is possible to obtain a maximum likelihood solution of this identification problem, by means of a two-step iterative algorithm. This approach allows also to estimate, as a byproduct, the noise-free input and output sequences. Moreover, an analytic expression of the finite Cramer-Rao lower bound is derived. The method does not require any particular assumption on the input process, however the ratio of the noise variances is assumed as known. The effectiveness of the proposed algorithm has been verified by means of Monte Carlo simulations.
2007
R. Diversi, R. Guidorzi, U. Soverini (2007). Maximum likelihood identification of noisy input-output models. AUTOMATICA, 43, 464-472 [10.1016/j.automatica.2006.09.009].
R. Diversi; R. Guidorzi; U. Soverini
File in questo prodotto:
Eventuali allegati, non sono esposti

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/11585/37765
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 47
  • ???jsp.display-item.citation.isi??? 34
social impact