DocumentCode
3068942
Title
Multichannel relative-entropy spectrum analysis
Author
Johnson, Rodney W. ; Musicus, Bruce R.
Author_Institution
Naval Research Laboratory, Washington, D.C., U.S.A.
Volume
9
fYear
1984
fDate
30742
Firstpage
550
Lastpage
553
Abstract
A new method is presented for estimating the power spectral density matrix for multichannel data, given correlation values for linear combinations of the channels and given an initial estimate of the spectral density matrix. A derivation of the method from the relative-entropy principle is given. The results differ significantly from the Multisignal Relative-Entropy ("Minimum-Cross-Entropy") Spectrum Analysis of Johnson and Shore because the present method does not arbitrarily force the final distributions of the various channels to be independent. For the special case when correlation values are given only for the sum of the channels, Multichannel Relative-Entropy Spectrum Analysis is shown to reduce to a two-stage procedure: first a smooth power-spectrum model is fitted to the correlations of the sum; then final estimates of the spectra and cross spectra are obtained through linear filtering. Illustrative numerical examples are presented.
Keywords
Autocorrelation; Entropy; Filtering; Lagrangian functions; Maximum likelihood detection; Probability distribution; Spectral analysis; State estimation; Wiener filter; Yield estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '84.
Type
conf
DOI
10.1109/ICASSP.1984.1172301
Filename
1172301
Link To Document