Analysis of dimension reduction by PCA and AdaBoost on spelling paradigm EEG data

@article{Yildirim2013AnalysisOD,
  title={Analysis of dimension reduction by PCA and AdaBoost on spelling paradigm EEG data},
  author={Asil Yildirim and Ugur Halici},
  journal={2013 6th International Conference on Biomedical Engineering and Informatics},
  year={2013},
  pages={192-196}
}
Spelling Paradigm is a BCI application which aims to construct words by finding letters using P300 signals recorded via channel electrodes attached to the diverse points of the scalp. In this study effects of dimension reduction using Principal Component Analysis (PCA) and AdaBoost methods on time domain characteristics of P300 evoked potentials in Spelling Paradigm are analyzed. Support Vector Machine (SVM) is used for classification. 
1 Citations
9 References
Similar Papers

Citations

Publications citing this paper.

References

Publications referenced by this paper.
Showing 1-9 of 9 references

BCI Competition II (2003) – P300 Speller Dataset Webpage”, [Online] Available: http://www.bbci.de/competition/ii/, Documentation:http://www.bbci.de/competition/ii/albany_desc/albany_d esc_ii.pdf

  • B. Blankertz
  • 2010
2 Excerpts

BCI Competition III (2005) – P300 Speller Dataset Webpage”, [Online] Available: http://www.bbci.de/competition/iii/, Documentation: http://www.bbci.de/competition/iii/desc_II.pdf

  • B. Blankertz
  • 2010
1 Excerpt

Similar Papers

Loading similar papers…