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NEURONAL SPIKE TRAIN DECODING FOR THE BRAIN-COMPUTER INTERFACE USING NONLINEAR FILTER BASED ON SUPPORT VECTOR MACHINE

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dc.contributor.authorKim, SS-
dc.contributor.authorKim, KH-
dc.contributor.authorKim, Sung June-
dc.date.accessioned2009-08-26T02:41:59Z-
dc.date.available2009-08-26T02:41:59Z-
dc.date.issued2004-12-01-
dc.identifier.citation제7회 한국뇌신경학회 학술대회, 서울대학교, 2004년 12월 1일en
dc.identifier.urihttp://www.ksbns.org/abstract/2004_fall/green/view.html?num=490-
dc.identifier.urihttps://hdl.handle.net/10371/7840-
dc.description.abstractFor the brain-computer interface based on the activities of multiple cortical neurons, the decoding algorithm, which extracts the information on the movement parameters encoded within the neuronal spike train, is essential. We devised and implemented several decoding algorithms based on linear and nonlinear filtering in order to confirm the necessity of the nonlinear filter. Their performances were evaluated under various conditions by changing the number of neurons within the spike train, the length and the frequency of input to the decoding algorithms, and type and rates of error for the spike detection and classification. We confirmed the general superiority of nonlinear filters. The support vector machine showed the highest performance.en
dc.language.isoenen
dc.publisher한국뇌신경과학회 = The Korean Society for Brain and Neural Scienceen
dc.subjectspike trainen
dc.subjecttrainingen
dc.subjecterror ratesen
dc.subjectdecoding performanceen
dc.subjectBCIen
dc.titleNEURONAL SPIKE TRAIN DECODING FOR THE BRAIN-COMPUTER INTERFACE USING NONLINEAR FILTER BASED ON SUPPORT VECTOR MACHINEen
dc.typeConference Paperen
dc.contributor.AlternativeAuthor김성준-
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