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Application of reliability-based automatic repeat request to multi-class classification for brain-computer interfaces
http://hdl.handle.net/2237/13908
http://hdl.handle.net/2237/139086c148ce8-8524-4458-86e6-fba799aa1521
| 名前 / ファイル | ライセンス | アクション |
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kokusai-0908-takahashi.pdf (150.1 kB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||
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| 公開日 | 2010-08-02 | |||||
| タイトル | ||||||
| タイトル | Application of reliability-based automatic repeat request to multi-class classification for brain-computer interfaces | |||||
| 言語 | en | |||||
| 著者 |
Takahashi, Hiromu
× Takahashi, Hiromu× Yoshikawa, Tomohiro× Furuhashi, Takeshi |
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| アクセス権 | ||||||
| アクセス権 | open access | |||||
| アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||
| 権利 | ||||||
| 言語 | en | |||||
| 権利情報 | ©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | |||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | A brain-computer interface (BCI) is a system which could enable patients like those with amyotrophic lateral sclerosis to control some equipment and to communicate with other people, and has been anticipated to be achieved. One of the problems in BCI research is a trade-off between transmission speed and accuracy. In the field of data transmission, on the other hand, reliability-based hybrid automatic repeat request (RB-HARQ), one of the error control methods, has been developed to achieve both of the performances. The authors, therefore, have considered BCIs as communications between users and computers, and applied reliability-based ARQ, customized RB-HARQ, to BCIs. It has been shown that the proposed method is superior to other error control methods in two-class classification. In this paper, the proposed method is extended to deal with multi-class classification of EEG data, and is shown to be effective in multi-class problems. | |||||
| 言語 | en | |||||
| 出版者 | ||||||
| 出版者 | IEEE | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプresource | http://purl.org/coar/resource_type/c_6501 | |||||
| タイプ | journal article | |||||
| 出版タイプ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
| DOI | ||||||
| 関連タイプ | isVersionOf | |||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | https://doi.org/10.1109/FUZZY.2009.5277224 | |||||
| ISSN | ||||||
| 収録物識別子タイプ | PISSN | |||||
| 収録物識別子 | 1098-7584 | |||||
| 書誌情報 |
en : IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2009) p. 1027-1032, 発行日 2009-08-20 |
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| フォーマット | ||||||
| 値 | application/pdf | |||||
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| 値 | publisher | |||||
| URI | ||||||
| 識別子 | http://hdl.handle.net/2237/13908 | |||||
| 識別子タイプ | HDL | |||||
| URI | ||||||
| 識別子 | http://dx.doi.org/10.1109/FUZZY.2009.5277224 | |||||
| 識別子タイプ | DOI | |||||
