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

Epileptic EEG signals recognition based on wavelet package and least square support vector machine

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

1 Author(s)
Zhou Hongbiao ; Fac. of Electron. & Electr. Eng., Huaiyin Inst. of Technol., Huaiyin, China

In order to extract the feature of epileptic EEG efficiently, and to improve the classification accuracy, a nonlinear feature extraction method based on wavelet packet Transform(WPT) and support vector machine(SVM) is proposed. The Samples are composed of five hundred EEG Public datum which include the Period of epileptic seizures. Character vectors which reflect different state of EEG signals are extracted from different frequency segments with the technology of wavelet packet decomposition which have the trait of arbitrary distinction and decomposition. The classifier is composed of the least square SVM(LSSVM) which trained by the characteristic vectors,its parameters are optimized by genetic algorithm(GA) and particle swarm optimization(PSO). Experimental results demonstrate that the classifier has good classification and generalization abilities, the identification rate of SVM which parameters are optimized by PSO algorithm reaches 91.50%.

Published in:

Control Conference (CCC), 2011 30th Chinese

Date of Conference:

22-24 July 2011

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.