DocumentCode
1488133
Title
An information theoretic spectral density
Author
Choi, Byoung-seon
Author_Institution
Dept. of Appl. Stat., Yonsei Univ., Seoul, South Korea
Volume
38
Issue
4
fYear
1990
fDate
4/1/1990 12:00:00 AM
Firstpage
717
Lastpage
721
Abstract
An information theoretic spectrum which minimizes the Kullback-Leibler (1951) information number subject to the first p +1 autocovariance terms is proposed. The KL spectrum includes the maximum-entropy spectrum and the ARMA (autoregressive moving-average) spectrum as special cases. A method is proposed for modifying a spectral estimate, on the basis of the results for the KL spectrum, so that the revised spectral estimate is more loyal to the given observations than the primary estimate
Keywords
information theory; spectral analysis; ARMA spectrum; autocovariance terms; autoregressive moving-average; information theory; maximum-entropy spectrum; spectral analysis; spectral density; spectral estimate; Acoustic signal processing; Constraint theory; Density measurement; Entropy; Equations; Frequency domain analysis; Probability; Speech processing; Statistics;
fLanguage
English
Journal_Title
Acoustics, Speech and Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
0096-3518
Type
jour
DOI
10.1109/29.52713
Filename
52713
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