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Analysis of Dimension Reduction by PCA and AdaBoost on Spelling Paradigm EEG Data
Date
2013-12-18
Author
YILDIRIM, Asil
Halıcı, Uğur
Metadata
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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.
Subject Keywords
Brain computer interfaces
,
Spelling paradigm
,
Principal component analysis
,
Adaboost
,
Support vector machines
URI
https://hdl.handle.net/11511/41930
DOI
https://doi.org/10.1109/bmei.2013.6746932
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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A. YILDIRIM and U. Halıcı, “Analysis of Dimension Reduction by PCA and AdaBoost on Spelling Paradigm EEG Data,” 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/41930.