Classification of EEG Signals Using a Multiple Kernel Learning Support Vector Machine

Classification of EEG Signals Using a Multiple Kernel Learning Support Vector Machine

In this study, a multiple kernel learning support vector machine algorithm is proposed for the identification of EEG signals including mental and cognitive tasks, which is a key component in EEG-based brain computer interface (BCI) systems. The presented BCI approach included three stages: (1) a pre...

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Bibliographic Details
Main Authors: Xiaoou Li, Xun Chen, Yuning Yan, Wenshi Wei, Z. Jane Wang
Format: Article
Language:English
Published: MDPI AG 2014-07-01
Series:Sensors
Subjects:
brain computer interface
mental task
stroke patients
multiple kernel learning
polynomial kernel
radial basis function kernel
Online Access:http://www.mdpi.com/1424-8220/14/7/12784

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