Title :
Comments on "A general method of minimum cross-entropy spectral estimation"
Author :
Burr, Robert L. ; Lytle, Dean W.
Author_Institution :
University of Washington, Seattle, WA
fDate :
10/1/1986 12:00:00 AM
Abstract :
In a recent correspondence Tzannes et al. [1] introduced a new form of minimum cross-entropy (MCE) spectral analysis based on the observation that normalized spectra and symmetric probability density functions (pdf´s) are axiomatically indistinguishable. Thus, the form of the minimum cross-entropy posterior pdf can be used as a model for spectral estimation. In this correspondence we derive the same result without using a Lagrange multiplier methodology. We also establish the connection of this estimate to the cepstral representation of the signal and propose an efficient algorithm not requiring explicit solution of nonlinear equations.
Keywords :
Autocorrelation; Cepstral analysis; Entropy; Exponential distribution; Frequency estimation; Lagrangian functions; Nonlinear equations; Probability density function; Spectral analysis; Speech processing;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
DOI :
10.1109/TASSP.1986.1164928