Identification of autoregressive models in the presence of additive noise

International Journal of Adaptive Control and Signal Processing

Volumn 22, Issue 5, 2008, Pages 465-481

  Diversi, Roberto ^a   Guidorzi, Roberto ^a   Soverini, Umberto ^a  

^a UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

Autoregressive models; System identification; Yule Walker equations

Indexed keywords

ALGORITHMS; ARGON; BOOLEAN FUNCTIONS; COSMIC RAY DETECTORS; ERROR ANALYSIS; ERRORS; ESTIMATION; FOOD ADDITIVES; FUNCTION EVALUATION; MONTE CARLO METHODS; REGRESSION ANALYSIS; SPURIOUS SIGNAL NOISE; TRANSFER FUNCTIONS;

(E ,3E) PROCESS; (MIN ,MAX ,+) FUNCTIONS; AR MODELING; AUTOCORRELATION MATRICES; AUTOREGRESSIVE (MAR) MODELING; ENGINEERING APPLICATIONS; EQUATION ERROR; HIGH ORDER; MONTE CARLO SIMULATION (MCS); NEW ALGORITHM; NOISE MODELLING; OBSERVATION NOISE; POSITIVE DEFINITENESS; YULE-WALKER EQUATIONS;

MODELS;

EID: 46749103366     PISSN: 08906327     EISSN: 10991115     Source Type: Journal    
DOI: 10.1002/acs.989     Document Type: Article

References (23)

1. Kay SM. Modem Spectral Estimation. Prentice-Hall: Englewood Cliffs, NJ, 1988.
2. Haykin S. Adaptive Filter Theory. Prentice-Hall: Englewood Cliffs, NJ, 1991.
3. Haykin S, Steinhardt A (eds). Adaptive Radar Detection and Estimation. Wiley-Interscience: New York, 1992.
4. Isermann R. Mechatronic Systems. Springer: Berlin, 2005.
5. Pagano M. Estimation of models of autoregressive signal plus white noise. Annals of Statistics 1974; 2:99-108.
6. Kay SM. The effects of noise on the autoregressive spectral estimator. IEEE Transactions on Acoustics, Speech and Signal Processing 1979; 27:478-485.
7. Tong H. Autoregressive model fitting with noisy data by Akaike's information criterion. IEEE Transactions on Information Theory 1975; 21:476-480.
8. Nehorai A, Stoica P. Adaptive algorithms for constrained ARMA signals in the presence of noise. IEEE Transactions on Acoustics, Speech and Signal Processing 1988; 36:1282-1291.
9. Kay SM. Noise compensation for autoregressive spectral estimates. IEEE Transactions on Acoustics, Speech and Signal Processing 1980; 28:292-303.
10. Chan YT, Langford RP. Spectral estimation via the high-order Yule-Walker equations. IEEE Transactions on Acoustics, Speech and Signal Processing 1982; 30:689-698.
11. Cadzow J. Spectral estimation: an overdetermined rational model equation approach. Proceedings of the IEEE 1982; 70:907-939.
12. Sen Lee T. Large sample identification and spectral estimation of noisy multivariate autoregressive processes. IEEE Transactions on Acoustics, Speech and Signal Processing 1983; 31:76-82.
13. Paliwal KK. A noise-compensated long correlation matching method for AR spectral estimation of noisy signals. Signal Processing 1988; 15:437-440.
14. Davila CE. A subspace approach to estimation of autoregressive parameters from noisy measurements. IEEE Transactions on Signal Processing 1998; 46:531-534.
15. Sakai H, Arase M. Recursive parameter estimation of an autoregressive process disturbed by white noise. International Journal of Control 1979; 30:949-966.
16. Zheng WX. A least-squares based method for autoregressive signals in the presence of noise. IEEE Transactions on Circuits and Systems-II 1999; 46:81-85.
17. Jia LJ, Kanae S, Yang ZJ, Wada K. On bias compensation estimation for noisy AR process. Proceedings of the 42nd IEEE Conference on Decision and Control, Maui, HI, U.S.A., December 2003; 405-410.
18. Zheng WX. Fast identification of autoregressive signals from noisy observations. IEEE Transactions on Circuits and Systems-II 2005; 52:43-48.
19. Diversi R, Soverini U, Guidorzi R. A new estimation approach for AR models in presence of noise. Preprints of the 16th IFAC World Congress, Prague, Czech Republic, July 2005.
20. Diversi R, Guidorzi R, Soverini U. A noise-compensated estimation scheme for AR processes. Proceedings of the 42nd IEEE Conference on Decision and Control and 8th European Control Conference, Seville, Spain, December 2005; 4146-4151.
21. Davila CE. On the noise-compensated Yule-Walker equations. IEEE Transactions on Signal Processing 2001; 49:1119-1121.
22. Söderström T, Stoica P. System Identification. Prentice-Hall: Cambridge, MA, 1989.
23. Andrews DF, Herzberg AM. Data - A Collection of Problems from Many Fields for the Student and Research Worker. Springer: New York, 1985.