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

Using genetic algorithms and k-nearest neighbour for automatic frequency band selection for signal classification

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 $31
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)
Rivero, D. ; Dept. of Inf. & Commun. Technol., Univ. of A Coruna, A Coruña, Spain ; Guo, L. ; Seoane, J.A. ; Dorado, J.

The classification of signals is usually based on the extraction of various features that subsequently will be used as an input to a classifier. These features are extracted as a result of the experts' prior knowledge, which may often involve a lack of the information necessary for an accurate classification in all cases. This study proposes a new technique, in which a genetic algorithm is used to automatically extract frequency-domain features from a set of signals, with no need of prior knowledge. This allows, first, to achieve greater accuracy in the classification of signals, and, secondly, to discover new data on the signals to be classified. This system was used to solve a well-known problem: classification of electroencephalogram (EEG) signals, and its results show a better performance in comparison with other works on the same problem.

Published in:

Signal Processing, IET  (Volume:6 ,  Issue: 3 )

Date of Publication:

May 2012

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.