Adaptive classification for Brain Computer Interface systems using Sequential Monte Carlo sampling.
Adaptive classification is a key function of Brain Computer Interfacing (BCI) systems. This paper proposes robust mathematical frameworks and their implementation for the on-line sequential classification of EEG signals in BCI systems. The proposed algorithms are extensions to the basic method of An...
| Główni autorzy: | , , , |
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| Format: | Journal article |
| Język: | English |
| Wydane: |
2009
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