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  • Title: BCI Competition 2003--Data set IIb: support vector machines for the P300 speller paradigm.
    Author: Kaper M, Meinicke P, Grossekathoefer U, Lingner T, Ritter H.
    Journal: IEEE Trans Biomed Eng; 2004 Jun; 51(6):1073-6. PubMed ID: 15188881.
    Abstract:
    We propose an approach to analyze data from the P300 speller paradigm using the machine-learning technique support vector machines. In a conservative classification scheme, we found the correct solution after five repetitions. While the classification within the competition is designed for offline analysis, our approach is also well-suited for a real-world online solution: It is fast, requires only 10 electrode positions and demands only a small amount of preprocessing.
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