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

Sinusoidal Noise Reduction Method Using Leaky LMS Algorithm

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

3 Author(s)

A technique that uses a prediction error filter for reducing sinusoidal noises from a noisy speech has been proposed previously. Since the prediction error filter can estimate the sinusoidal noise completely, the output becomes zero in a non-speech segment. After the prediction error filter converges, the update of the filter coefficients is stopped. Then the fixed prediction error filter can cancel the sinusoidal noises except for a speech signal in a speech segment. However, frequency characteristics of the filter depend on its prediction algorithm, and the coefficients may converge the values which gives degradation of the speech. In this paper, we propose a new noise reduction algorithm which is a kind of leaky LMS algorithm, so that the prediction error filter removes only the sinusoidal line spectrum without speech degradation

Published in:

Intelligent Signal Processing and Communications, 2006. ISPACS '06. International Symposium on

Date of Conference:

12-15 Dec. 2006

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.