DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kang, H | - |
dc.contributor.author | Nam, Y | - |
dc.contributor.author | Choi, S | - |
dc.date.accessioned | 2016-04-01T03:01:03Z | - |
dc.date.available | 2016-04-01T03:01:03Z | - |
dc.date.created | 2010-04-28 | - |
dc.date.issued | 2009-08 | - |
dc.identifier.issn | 1070-9908 | - |
dc.identifier.other | 2009-OAK-0000020897 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/26138 | - |
dc.description.abstract | Common spatial pattern (CSP) is a popular feature extraction method for electroencephalogram ( EEG) classification. Most of existing CSP-based methods exploit covariance matrices on a subject-by-subject basis so that inter-subject information is neglected. In this paper we present modifications of CSP for subject-to-subject transfer, where we exploit a linear combination of covariance matrices of subjects in consideration. We develop two methods to determine a composite covariance matrix that is a weighted sum of covariance matrices involving subjects, leading to composite CSP. Numerical experiments on dataset IVa in BCI competition III confirm that our composite CSP methods improve classification performance over the standard CSP (on a subject-by-subject basis), especially in the case of subjects with fewer number of training samples. | - |
dc.description.statementofresponsibility | X | - |
dc.language | English | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.relation.isPartOf | IEEE SIGNAL PROCESSING LETTERS | - |
dc.subject | Brain computer interface | - |
dc.subject | common spatial pattern | - |
dc.subject | EEG classification | - |
dc.subject | transfer learning | - |
dc.subject | SINGLE-TRIAL EEG | - |
dc.subject | COMMUNICATION | - |
dc.subject | MOVEMENT | - |
dc.subject | FILTERS | - |
dc.title | Composite Common Spatial Pattern for Subject-to-Subject Transfer | - |
dc.type | Article | - |
dc.contributor.college | 정보전자융합공학부 | - |
dc.identifier.doi | 10.1109/LSP.2009.2022557 | - |
dc.author.google | Kang, H | - |
dc.author.google | Nam, Y | - |
dc.author.google | Choi, S | - |
dc.relation.volume | 16 | - |
dc.relation.issue | 8 | - |
dc.relation.startpage | 683 | - |
dc.relation.lastpage | 686 | - |
dc.contributor.id | 10077620 | - |
dc.relation.journal | IEEE SIGNAL PROCESSING LETTERS | - |
dc.relation.index | SCI급, SCOPUS 등재논문 | - |
dc.relation.sci | SCIE | - |
dc.collections.name | Journal Papers | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | IEEE SIGNAL PROCESSING LETTERS, v.16, no.8, pp.683 - 686 | - |
dc.identifier.wosid | 000267945500003 | - |
dc.date.tcdate | 2019-02-01 | - |
dc.citation.endPage | 686 | - |
dc.citation.number | 8 | - |
dc.citation.startPage | 683 | - |
dc.citation.title | IEEE SIGNAL PROCESSING LETTERS | - |
dc.citation.volume | 16 | - |
dc.contributor.affiliatedAuthor | Choi, S | - |
dc.identifier.scopusid | 2-s2.0-67149094955 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.wostc | 60 | - |
dc.description.scptc | 65 | * |
dc.date.scptcdate | 2018-05-121 | * |
dc.type.docType | Article | - |
dc.subject.keywordPlus | SINGLE-TRIAL EEG | - |
dc.subject.keywordPlus | COMMUNICATION | - |
dc.subject.keywordPlus | MOVEMENT | - |
dc.subject.keywordPlus | FILTERS | - |
dc.subject.keywordAuthor | Brain computer interface | - |
dc.subject.keywordAuthor | common spatial pattern | - |
dc.subject.keywordAuthor | EEG classification | - |
dc.subject.keywordAuthor | transfer learning | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
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