In this paper, we analyze the convergence of an iterative selftraining semi-supervised support vector machine (SVM) algorithm, which is designed for classi cation in small trainin...
Research on EEG based brain-computer-interfaces (BCIs) aims at steering devices by thought. Even for simple applications, BCIs require an extremely effective data processing to wo...
Christian Liefhold, Moritz Grosse-Wentrup, Klaus G...
Abstract. 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 ...
Alain Rakotomamonjy, Vincent Guigue, G. Mallet, V....
Musicians and composers have been using brainwaves as generative sources in music for at least 40 years and the possibility of a brain-computer interface for direct communication ...
The aim of this paper is to show that machine learning techniques can be used to derive a classifying function for human brain signal data measured by magnetoencephalography (MEG)...