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| Adaptive Spatial Filter Based on ERD/ERS for Brain-Computer Interfaces |
| Lü Jun; Xie Sheng-li; Zhang Jin-long |
| School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, China |
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Abstract For motor related Brain-Computer Interface (BCI), if the sample size is small, Common Spatial Patterns (CSP) algorithm is sensitive to outlier data and lacks of robustness. In this paper, an Adaptive Spatial Filter (ASF) algorithm is proposed to take filtered samples’ variances as the features and seek the spatial filter to maximize the ratio of two classes’ means. Unlike CSP, ASF is an iterative algorithm and have soft determination. ASF can adaptively decrease outliers’ effects according to the updated filters. Using two datasets from BCI competition 2003 and 2005, the experimental results show that ASF outperforms CSP，especially when training samples are few.
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Received: 13 September 2007
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2009, Vol. 31 
