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
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