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Semi-Supervised Learning Based on Manifold in BCI

Ji-Ying Zhong Xu Lei De-Zhong Yao

中国电子科技2009，Vol.7Issue(1)：22-26,5.

Semi-Supervised Learning Based on Manifold in BCI

Ji-Ying Zhong ¹Xu Lei ¹De-Zhong Yao¹

作者信息

1. Key Laboratory for NeuroInformation of Ministry of Education,School of Life Science and Technology,University of Electronic Science and Technology of China,Chengdu,610054,China
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摘要

Abstract

A Laplacian support vector machine (LapSVM) algorithm,a semi-supervised learning based on manifold,is introduced to brain-computer interface (BCI) to raise the classification precision and reduce the subjects' training complexity.The data are collected from three subjects in a three-task mental imagery experiment.LapSVM and transductive SVM (TSVM) are trained with a few labeled samples and a large number of unlabeled samples.The results confirm that LapSVM has a much better classification than TSVM.

关键词

Brain-computer interface/manifold learning/semi-supervised learning/support vector machine

Key words

Brain-computer interface/manifold learning/semi-supervised learning/support vector machine

分类

信息技术与安全科学

引用本文复制引用

Ji-Ying Zhong,Xu Lei,De-Zhong Yao..Semi-Supervised Learning Based on Manifold in BCI[J].中国电子科技,2009,7(1):22-26,5.

基金项目

This work was supported by the National Natural Science Foundation of China under Grant No.30525030, 60701015, and 60736029. （）

中国电子科技

ISSN：1674-862X

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