TY  - JOUR
A1  - Parra, L.
A1  - Spence, C.
A1  - Sajda, P.
A1  - Ziehe, Andreas
A1  - Müller, Klaus-Robert
T1  - Unmixing hyperspectral data
Y1  - 2000
ER  - 
TY  - JOUR
A1  - Kohlmorgen, J.
A1  - Müller, Klaus-Robert
A1  - Rittweger, J.
A1  - Pawelzik, K.
T1  - Identification of nonstationary dynamics in physiological recordings
Y1  - 2000
ER  - 
TY  - JOUR
A1  - Mika, Sebastian
A1  - Rätsch, Gunnar
A1  - Weston, J.
A1  - Schölkopf, B.
A1  - Smola, Alexander J.
A1  - Müller, Klaus-Robert
T1  - Invariant feature extraction and classification in kernel spaces
Y1  - 2000
ER  - 
TY  - JOUR
A1  - Rätsch, Gunnar
A1  - Schölkopf, B.
A1  - Smola, Alexander J.
A1  - Mika, Sebastian
A1  - Onoda, T.
A1  - Müller, Klaus-Robert
T1  - Robust ensemble learning for data analysis
Y1  - 2000
ER  - 
TY  - JOUR
A1  - Onoda, T.
A1  - Rätsch, Gunnar
A1  - Müller, Klaus-Robert
T1  - An asymptotic analysis and improvement of AdaBoost in the binary classification case (in Japanese)
Y1  - 2000
ER  - 
TY  - JOUR
A1  - Dornhege, Guido
A1  - Blankertz, Benjamin
A1  - Krauledat, Matthias
A1  - Losch, Florian
A1  - Curio, Gabriel
A1  - Müller, Klaus-Robert
T1  - Combined optimization of spatial and temporal filters for improving brain-computer interfacing
JF  - IEEE transactions on bio-medical electronics
N2  - Brain-computer interface (BCI) systems create a novel communication channel from the brain to an output de ice by bypassing conventional motor output pathways of nerves and muscles. Therefore they could provide a new communication and control option for paralyzed patients. Modern BCI technology is essentially based on techniques for the classification of single-trial brain signals. Here we present a novel technique that allows the simultaneous optimization of a spatial and a spectral filter enhancing discriminability rates of multichannel EEG single-trials. The evaluation of 60 experiments involving 22 different subjects demonstrates the significant superiority of the proposed algorithm over to its classical counterpart: the median classification error rate was decreased by 11%. Apart from the enhanced classification, the spatial and/or the spectral filter that are determined by the algorithm can also be used for further analysis of the data, e.g., for source localization of the respective brain rhythms.
KW  - brain-computer interface
KW  - common spatial patterns
KW  - EEG
KW  - event-related desynchronization
KW  - single-trial-analysis
Y1  - 2006
U6  - https://doi.org/10.1109/TBME.2006.883649
SN  - 0018-9294
VL  - 53
IS  - 11
SP  - 2274
EP  - 2281
PB  - IEEE
CY  - New York
ER  -