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The MLSP competition (2010) purpose is to design a pattern recognition system for “mind reading”. This paper is a study of the EEG competition dataset and the crafting of the third place winning method. It shortly presents our signal processing methods for feature extraction, and channel selection. We accurately tuned all the parameters of(More)
We investigate the benefit of combining both cluster assumption and manifold assumption underlying most of the semi-supervised algorithms using the flexibility and the efficiency of multi-kernel learning. The multiple kernel version of Transductive SVM (a cluster assumption based approach) is proposed and it is solved based on DC (Difference of Convex(More)
The objective of the paper is to investigate the effect of subject's emotional states on Brain Computer Interface (BCI) performance. Two psycho-physiological experiments are designed and implemented. The first one induces subjects' emotion using video clips first, then involves subjects' in SSVEP task. The second one induces subjects' emotions and SSVEP(More)
Brain-computer Interface (BCI) has achieved numerous successful applications in both clinical domain and daily life amelioration. As an essential component, signal processing determines markedly the performance of a BCI system. In this thesis, we dedicate to improve the signal processing strategy from perspective of machine learning strategy. Firstly, we(More)
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