Brain-Computer Interface: Common Tensor Discriminant Analysis Classifier Evaluation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F11%3A00365748" target="_blank" >RIV/67985807:_____/11:00365748 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/NaBIC.2011.6089732" target="_blank" >http://dx.doi.org/10.1109/NaBIC.2011.6089732</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/NaBIC.2011.6089732" target="_blank" >10.1109/NaBIC.2011.6089732</a>

Result language
angličtina
Original language name
Brain-Computer Interface: Common Tensor Discriminant Analysis Classifier Evaluation
Original language description
The performance of the Common Tensor Discriminant Analysis CTDA method for Brain-Computer Interface EEG pattern classification is compared with three other classifiers. The classifiers are designed with the aim to distinguish EEG patterns appearing as aresult of performance of several mental tasks. Classifier comparison has yielded quite similar results as regards our experimental imagery movement data set as well as for BCI Competition IV data set. The Bayesian and Multiclass Common Spatial Patterns classifiers, which use solely interchannel covariance as input, are shown to be comparable in performance, while lagging behind the Multiclass Common Spatial Patterns classifier and the CTDA classifier, that is classifiers which additionally account for EEG frequency structure. It is shown that the CTDA classifier and the Multiclass Common Spatial Patterns classifier provide significantly better classification than other two methods but at a higher computational cost.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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