Inhalt des Dokuments
All Publications by GRK Members
| Citation key | Samek20110 |
|---|---|
| Author | Samek, W., Kawanabe, M., and Vidaurre, C. |
| Title of Book | Proceedings of 5th International Brain-Computer Interface Conference 2011 |
| Year | 2011 |
| Abstract | In this paper we present an extension of the recently proposed Stationary Subspace Analy- sis (SSA). This novel method solves the problem how to group signals from different conditions and/or subjects to find stationary subspaces. The original SSA approach does not offer a natural way to group data and therefore better define the non-stationarities of interest. This drawback is solved with group-wise SSA (gwSSA) and demonstrated with a simple but illustrative example: the classification of BCI data. If not treated correctly the BCI tasks are considered as non-stationarities in SSA, which complicates its use for classification purposes. We show how, by correctly defining groups, non-stationarities of interest can be extracted. In this paper, the application is in multi-class signals, where the groups are properly defined to even improve classification performance. |
Import Publication
Export all entries to BibTexZusatzinformationen / Extras
Quick Access:
Schnellnavigation zur Seite über Nummerneingabe