DocumentCode
899782
Title
On the asymptotic statistical behavior of empirical cepstral coefficients
Author
Merhav, Neri ; Lee, Chin-Hui
Author_Institution
Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel
Volume
41
Issue
5
fYear
1993
fDate
5/1/1993 12:00:00 AM
Firstpage
1990
Lastpage
1993
Abstract
The asymptotic covariance matrix of the empirical cepstrum is analyzed. It is shown that for Gaussian processes, ceptral coefficients derived from smoothed periodograms are asymptotically uncorrelated and their variances multiplied by the sample size tend to unity. For an autoregressive process and its autoregressive cepstrum estimate, somewhat weaker results hold
Keywords
spectral analysis; speech recognition; statistical analysis; Gaussian processes; asymptotic covariance matrix; asymptotic statistical behavior; autoregressive cepstrum estimate; autoregressive process; empirical cepstral coefficients; smoothed periodograms; speech recognition; Autoregressive processes; Cepstral analysis; Cepstrum; Convergence; Covariance matrix; Gaussian processes; Optical reflection; Random processes; Speech processing; Speech recognition;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.215323
Filename
215323
Link To Document