Sciweavers

Share
ICA
2010
Springer

Riemannian Geometry Applied to BCI Classification

11 years 12 months ago
Riemannian Geometry Applied to BCI Classification
Abstract. In brain computer interface based on motor imagery, covariances matrices are widely used through spatial filters computation and other signal processing methods. Covariances matrices lie in the space of Semi-definite Positives (SPD) matrices and therefore, fall within the Riemannian geometry domain. Using a differential geometry frameworks, we propose different algorithms in order to classify covariances matrices in their native space.
Alexandre Barachant, Stéphane Bonnet, Marco
Added 11 Feb 2011
Updated 11 Feb 2011
Type Journal
Year 2010
Where ICA
Authors Alexandre Barachant, Stéphane Bonnet, Marco Congedo, Christian Jutten
Comments (0)
books