DocumentCode
1591237
Title
Facts and fiction in spectral analysis
Author
Broersen, P.M.T.
Author_Institution
Dept. of Appl. Phys., Delft Univ. of Technol., Netherlands
Volume
2
fYear
1998
Firstpage
1325
Abstract
This analysis is limited to the spectral density of unknown stationary stochastic processes. The main estimation methods are parametric with time series, or non-parametric with a Fourier transform of the data. A single time series model is chosen automatically from the three selected models: the best autoregressive, AR, the best moving average, MA and the best combined ARMA. The accuracy of the spectrum, computed from this single ARMA time series model, is compared with the accuracy of windowed periodogram estimates. The time series model generally gives a spectrum that is better than the best periodogram. It is a fact that a single time series model can be selected automatically for unknown statistical data. It is fiction to believe that objective choices between windowed periodograms can be made
Keywords
Fourier transforms; autoregressive moving average processes; estimation theory; spectral analysis; time series; ARMA; Fourier transform; autoregressive; moving average; nonparametric estimation methods; parametric estimation methods; spectral analysis; spectral density; time series; unknown stationary stochastic processes; unknown statistical data; windowed periodogram estimates; Books; Electronic switching systems; Fourier transforms; Physics; Signal processing; Spectral analysis; Stochastic processes; Time series analysis; White noise; World Wide Web;
fLanguage
English
Publisher
ieee
Conference_Titel
Instrumentation and Measurement Technology Conference, 1998. IMTC/98. Conference Proceedings. IEEE
Conference_Location
St. Paul, MN
ISSN
1091-5281
Print_ISBN
0-7803-4797-8
Type
conf
DOI
10.1109/IMTC.1998.676966
Filename
676966
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