EEG classification using generative independent component analysis
نویسندگان
چکیده
منابع مشابه
EEG classification using generative independent component analysis
We present an application of independent component analysis (ICA) to the discrimination of mental tasks for EEG-based brain computer interface systems. ICA is most commonly used with EEG for artifact identification with little work on the use of ICA for direct discrimination of different types of EEG signals. By viewing ICA as a generative model, we can use Bayes’ rule to form a classifier. We ...
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We present an application of Independent Component Analysis (ICA) to the discrimination of mental tasks for EEG-based Brain Computer Interface systems. ICA is most commonly used with EEG for artifact identification with little work on the use of ICA for direct discrimination of different types of EEG signals. By viewing ICA as a generative model, we can use Bayes’ rule to form a classifier. Thi...
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ژورنال
عنوان ژورنال: Neurocomputing
سال: 2006
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2005.12.028