Multi-sphere support vector data description for brain-computer interface

Phuoc Nguyen, Dat Tran, Trung Le, Tuan Hoang, Dharmendra Sharma

Research output: A Conference proceeding or a Chapter in BookConference contribution

6 Citations (Scopus)

Abstract

Support vector data description (SVDD) has been widely used in pattern classification, however it does not provide high performance in brain-computer interface (BCI) classification problems since brain signals are noisy and chaotic. Brain data have distinct distributions and hence a hyper-sphere in SVDD could not well describe the data. We propose in this paper a multi-sphere approach to SVDD to have a better description for the brain data. We also propose a fuzzy clustering approach to optimize SVDD parameters. Experiments on the brain data set III for motor imagery problem in BCI Competition II were conducted to compare performance of SVDD and multi-sphere SVDD
Original languageEnglish
Title of host publicationThe 4th International Conference on Communications Electronics (ICCE)
EditorsNguyen Xuan Quynh, Jinwoo Park, Roberto D.Graglia
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages318-321
Number of pages4
ISBN (Print)9781467324915
DOIs
Publication statusPublished - 2012
Event4th International Conference on Communications & Electronics (ICCE) - Hue, Hue, Viet Nam
Duration: 1 Aug 20123 Aug 2012

Conference

Conference4th International Conference on Communications & Electronics (ICCE)
Abbreviated titleICCE 2012
CountryViet Nam
CityHue
Period1/08/123/08/12

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Nguyen, P., Tran, D., Le, T., Hoang, T., & Sharma, D. (2012). Multi-sphere support vector data description for brain-computer interface. In N. X. Quynh, J. Park, & R. D.Graglia (Eds.), The 4th International Conference on Communications Electronics (ICCE) (pp. 318-321). USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CCE.2012.6315920