DocumentCode
1178989
Title
AR model order selection based on bispectral cross correlation
Author
Noonan, J. ; Premus, V. ; Irza, J.
Author_Institution
Dept. of Electr. Eng., Tufts Univ., Medford, MA, USA
Volume
39
Issue
6
fYear
1991
fDate
6/1/1991 12:00:00 AM
Firstpage
1440
Lastpage
1442
Abstract
A novel method is presented for optimal model order selection for autoregressive (AR) bispectrum estimation. The method depends solely on the data and requires no a priori information about the process. The method selects the model order that maximizes the cross correlation between the direct (fast Fourier transform-based) bispectrum estimate and the autoregressive bispectrum estimate. Simulation results are reviewed which demonstrate the method´s performance for the case of quadratically coupled sinusoids embedded in white Gaussian noise
Keywords
correlation theory; fast Fourier transforms; spectral analysis; white noise; AR bispectrum estimation; AR model; FFT; autoregressive bispectrum estimate; bispectral cross correlation; fast Fourier transform; optimal model order selection; performance; quadratically coupled sinusoids; simulation results; white Gaussian noise; Autocorrelation; Frequency estimation; Gaussian noise; Inspection; Laboratories; Optimization methods; Power measurement; Signal to noise ratio; Testing;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.136555
Filename
136555
Link To Document