DocumentCode :
1205075
Title :
The fast Fourier transform for experimentalists, part IV: autoregressive spectral analysis
Author :
Rust, B. ; Donnelly, David
Author_Institution :
US National Institute for Standards and Technology
Volume :
7
Issue :
6
fYear :
2005
Firstpage :
85
Lastpage :
90
Abstract :
We consider two additional kinds of spectrum estimates: autoregressive (AR) estimates and the maximum entropy (ME) method. In the first approach, we assume that an AR process generates the time series, which means we can compute the PSD of the time series from estimates of the AR parameters. The second approach is a special case of the first, but it uses a different method for estimating the AR parameters. Specifically, it chooses them to make the PSD´s inverse transform compatible with the measured time series, while remaining maximally noncommittal about the data outside the observational window.
Keywords :
autoregressive processes; fast Fourier transforms; maximum entropy methods; spectral analysis; time series; autoregressive spectral analysis; correlogram estimator; fast Fourier transform; inverse transform; maximum entropy method; periodogram estimator; power spectral density function; spectrum estimation; time series; Computer aided software engineering; Equations; Fast Fourier transforms; Frequency estimation; IEEE Spectrum Editorial Board; Linear systems; Physics; Spectral analysis; Symmetric matrices; Winches; FFT; autoregression; fast Fourier transform; maximum entropy;
fLanguage :
English
Journal_Title :
Computing in Science & Engineering
Publisher :
ieee
ISSN :
1521-9615
Type :
jour
DOI :
10.1109/MCSE.2005.126
Filename :
1524863
Link To Document :
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