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2006
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An Improved Semi-Supervised Support Vector Machine Based Translation Algorithm for BCI Systems

8 years 10 months ago
An Improved Semi-Supervised Support Vector Machine Based Translation Algorithm for BCI Systems
In this study, we propose an improved semi-supervised support vector machine (SVM) based translation algorithm for brain-computer interface (BCI) systems, aiming at reducing the time-consuming training process and enhancing the adaptability of BCI systems. In this algorithm, we apply a semi-supervised SVM, which builds a SVM classifier based on small amounts of labeled data and large amounts of unlabeled data, to translating the features extracted from the electrical recordings of brain into control signals. For reducing the time to train the semi-supervised SVM, we improve it by introducing an batch-mode incremental training method, which also can be used to enhance the adaptability of online BCI systems. The off-line data analysis results demonstrated the effectiveness of our algorithm.
Jianzhao Qin, Yuanqing Li
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where ICPR
Authors Jianzhao Qin, Yuanqing Li
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