Abstract
Since each ICA algorithm employs a different approach for source estimation, the result of the estimated sources could be changed. The proposed evaluation method applies three different ICA algorithms on EEG datasets including FastICA, Infomax and Extended-Infomax algorithms. The analysis demonstrates that different ICA algorithms do not have a significant effect on the accuracy of the Support Vector Machine (SVM) classifier in detecting right and left hand imagery movements.
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Zakeri, M., Zakeri, Z. (2013). Evaluation of Independent Component Analysis Algorithms for Electroencephalography Source Separation. In: Stephanidis, C. (eds) HCI International 2013 - Posters’ Extended Abstracts. HCI 2013. Communications in Computer and Information Science, vol 373. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39473-7_125
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DOI: https://doi.org/10.1007/978-3-642-39473-7_125
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