Title :
Time series analysis in the frequency domain
Author :
Pintelon, Rik ; Schoukens, J.
Author_Institution :
Vrije Univ., Brussels, Belgium
fDate :
1/1/1999 12:00:00 AM
Abstract :
This correspondence presents a parametric frequency domain identification algorithm for autoregressive moving average (ARMA) processes that does not suffer from spectral leakage errors. It is based on an extended transfer function model that takes into account the begin and end effect of the finite data record. The relationship with the one-step-ahead prediction error method is established. The advantages of the proposed method are easy prefiltering and leakage-free spectral representation of the raw data
Keywords :
autoregressive moving average processes; frequency-domain analysis; identification; signal representation; spectral analysis; time series; transfer functions; ARMA processes; autoregressive moving average processes; extended transfer function model; finite data record; frequency domain; leakage-free spectral representation; one-step-ahead prediction error method; parametric frequency domain identification algorithm; prefiltering; time series analysis; Autoregressive processes; Discrete Fourier transforms; Filters; Frequency domain analysis; Least squares approximation; Parameter estimation; Polynomials; Reactive power; Signal processing algorithms; Time series analysis;
Journal_Title :
Signal Processing, IEEE Transactions on
