Cart (Loading....) | Create Account
Close category search window
 

Reduced rank predictive source coding

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Witzgall, H.E. ; Sci. Applications Int. Corp., Chantilly, VA, USA ; Goldstein, J.S.

This paper introduces reduced rank statistical processing to residual error linear predictive source coding. A reduced rank predictive weight vector is generated using the reduced order correlation kernel estimation technique (ROCKET). The results illustrate a significant reduction in the reconstruction error of a reduced rank filter when the residual error is corrupted by noise. The noise may be due to either quantization noise or channel noise. The analysis shows that a filter's impulse response determines the impact of noise on its signal reconstruction and it is the ability of the predictive filter to alter its impulse response as a function of rank, which improves its performance. The results are demonstrated on recorded speech data and compared with the conventional Levinson-Durbin algorithm. Finally it is interesting to note that the reason for this reduced rank performance gain is not related to limited training data for the predictive filter.

Published in:

Statistical Signal Processing, 2003 IEEE Workshop on

Date of Conference:

28 Sept.-1 Oct. 2003

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.