Adaptive Multiclass Classification for Brain Computer Interfaces
نویسندگان
چکیده
منابع مشابه
Adaptive Multiclass Classification for Brain Computer Interfaces
We consider the problem of multiclass adaptive classification for brain-computer interfaces and propose the use of multiclass pooled mean linear discriminant analysis (MPMLDA), a multiclass generalization of the adaptation rule introduced by Vidaurre, Kawanabe, von Bünau, Blankertz, and Müller (2010) for the binary class setting. Using publicly available EEG data sets and tangent space mapping ...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2014
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco_a_00592