Title :
An information theoretic spectral density
Author :
Choi, Byoung-seon
Author_Institution :
Dept. of Appl. Stat., Yonsei Univ., Seoul, South Korea
fDate :
4/1/1990 12:00:00 AM
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;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
