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

An auditory classifier employing a wavelet neural network implemented in a digital design

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

4 Author(s)
Hughes, J. ; Rochester Inst. of Technol., Motorola, Austin, TX, USA ; Gaborski, R. ; Hsu, K. ; Titus, A.

This work explores the use of a wavelet transform, a feature extractor mechanism, and a neural network to classify audio samples as belonging to either a voice class, or a music class. The proposed system was implemented in a digital design using VHDL and was synthesized with the Synopsys Design Compiler, using the LSI-10 K synthesized library cells with a clock frequency of 11.025 kHz. This design of a wavelet neural network was effective in correctly identifying the test data sets

Published in:

ASIC/SOC Conference, 2001. Proceedings. 14th Annual IEEE International

Date of Conference:

2001

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.