DocumentCode :
925105
Title :
The cross-bicepstrum: definition, properties, and application for simultaneous reconstruction of three nonminimum phase signals
Author :
Brooks, Dana H. ; Nikias, Chrysostomos L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA
Volume :
41
Issue :
7
fYear :
1993
fDate :
7/1/1993 12:00:00 AM
Firstpage :
2389
Lastpage :
2404
Abstract :
The recovery of three signals from their cross-bispectrum (or the identification of the impulse responses of three parallel linear time-invariant (LTI) systems from the cross-bispectrum of their system outputs) by computing the complex cepstrum of the cross-bispectrum, as long as the signals (or impulse responses) have no zeros on the unit circle, is discussed. It is shown that the three signals can be separated completely and (approximately) recovered in the cross-bicepstrum domain, except for their magnitude and linear phase factors. The computation of the cross-bicepstrum can be seen as a method for the simultaneous computation of the ordinary complex cepstra of three nonminimum-phase signals without the need for phase unwrapping. Both least-squares and fast Fourier-transform (FFT)-based methods for computing the bicepstral coefficients are presented. Simulation examples of signal reconstruction in Gaussian white and nonGaussian colored noise and of system identification are included. The results are extended to nth-order cross-spectra, and the factorization problem for these spectra is discussed
Keywords :
fast Fourier transforms; least squares approximations; parameter estimation; random noise; signal processing; spectral analysis; FFT; Gaussian white noise; bicepstral coefficients; complex cepstrum; cross-bicepstrum; factorization problem; fast Fourier-transform; least squares methods; nonGaussian colored noise; nth-order cross-spectra; signal processing; signal reconstruction; system identification; three nonminimum phase signals; Additive noise; Cepstrum; Colored noise; Computational modeling; Concurrent computing; Least squares methods; Poles and zeros; Signal processing; Signal reconstruction; System identification;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/78.224248
Filename :
224248
Link To Document :
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