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Konferenzbeitrag

MLSP Competition, 2010: Description of first place method

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84047

Leiva,  JM
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84076

Martens,  SMM
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Leiva, J., & Martens, S. (2010). MLSP Competition, 2010: Description of first place method. In 2010 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2010) (pp. 112-113). Piscataway, NJ, USA: IEEE.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-BE6C-2
Zusammenfassung
Our winning approach to the 2010 MLSP Competition is based on a generative method for P300-based BCI decoding, successfully applied to visual spellers. Here, generative has a double meaning. On the one hand, we work with a probability density model of the data given the target/non target labeling, as opposed to discriminative (e.g. SVM-based) methods. On the other hand, the natural consequence of this approach is a decoding based on comparing the observation to templates generated from the data.