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

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

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7 Citations (Scopus)


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 publication2012 Fourth International Conference on Communications and Electronics (ICCE)
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages4
ISBN (Print)9781467324939
Publication statusPublished - 2012
Externally publishedYes
EventInternational Conference on Communications and Electronics (HUT-ICCE) 2012 - Hue, Vietnam
Duration: 1 Aug 20123 Aug 2012
Conference number: 4th (Proceedings)


ConferenceInternational Conference on Communications and Electronics (HUT-ICCE) 2012
Abbreviated titleHUT-ICCE 2012
Internet address

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