Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization
Joint Authors
She, Qingshan
Ma, Yuliang
Luo, Zhizeng
Ding, Xiaohui
Potter, Thomas
Zhang, Yingchun
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-05-30
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters.
In this study, we propose using a particle swarm optimization algorithm to optimize the selection of both the kernel and penalty parameters in order to improve the classification performance of support vector machines.
The performance of the optimized classifier was evaluated with motor imagery EEG signals in terms of both classification and prediction.
Results show that the optimized classifier can significantly improve the classification accuracy of motor imagery EEG signals.
American Psychological Association (APA)
Ma, Yuliang& Ding, Xiaohui& She, Qingshan& Luo, Zhizeng& Potter, Thomas& Zhang, Yingchun. 2016. Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization. Computational and Mathematical Methods in Medicine،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1100142
Modern Language Association (MLA)
Ma, Yuliang…[et al.]. Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization. Computational and Mathematical Methods in Medicine No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1100142
American Medical Association (AMA)
Ma, Yuliang& Ding, Xiaohui& She, Qingshan& Luo, Zhizeng& Potter, Thomas& Zhang, Yingchun. Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization. Computational and Mathematical Methods in Medicine. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1100142
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1100142