Ensemble of SVMs for improving Brain Computer Interface P300 speller performances
Alain Rakotomamonjy, Vincent Guigue, Gregory Mallet and Victor Alvarado
In: International Conference on Artificial Neural Networks, Warsaw(2005).
This paper addresses the problem of signal responses variability
within a single subject in P300 speller Brain-Computer Interfaces.
We propose here a method to cope with these variabilities by considering
a single learner for each acquisition session. Each learner consists of
a channel selection procedure and a classifier. Our algorithm has been
benchmarked with the data and the results of the BCI 2003 competition
dataset and we clearly show that our approach yields to state-of-the art