Title :
An ARMA system identification scheme in the presence of noise
Author :
Fattah, S.A. ; Zhu, W.P. ; Ahmad, M.O.
Author_Institution :
Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, QC
Abstract :
This paper presents a scheme for the identification of minimum-phase autoregressive moving average (ARMA) systems in the presence of noise. For the identification of the AR part, we propose to repeat the correlation operation on an enhanced autocorrelation function of the observed signal based on a decision criterion and then employ the resultant to an extended form of Yule-Walker equations. A frequency domain noise-compensation scheme is introduced which operates on the noise-contaminated residual signal. The MA parameters are then estimated via the spectral factorization performed on the power spectrum of the noise-compensated residual signal. Computer simulations exhibit a superior estimation performance even at low levels of signal-to-noise ratio (SNR).
Keywords :
autoregressive moving average processes; correlation methods; decision theory; digital simulation; frequency-domain analysis; matrix decomposition; noise; spectral analysis; Yule-Walker equations; autocorrelation function; autoregressive moving average system identification scheme; computer simulations; decision criterion; frequency domain noise-compensation scheme; noise-contaminated residual signal; power spectrum; signal-to-noise ratio; spectral factorization; Autocorrelation; Equations; Frequency domain analysis; Noise reduction; Parameter estimation; Signal processing; Signal processing algorithms; Signal to noise ratio; System identification; Working environment noise;
Conference_Titel :
Circuits and Systems, 2007. NEWCAS 2007. IEEE Northeast Workshop on
Conference_Location :
Montreal, Que
Print_ISBN :
978-1-4244-1163-4
Electronic_ISBN :
978-1-4244-1164-1
DOI :
10.1109/NEWCAS.2007.4487976
