{"created":"2023-07-27T06:54:41.658296+00:00","id":50121,"links":{},"metadata":{"_buckets":{"deposit":"0aad6ea0-6be7-4d05-bc51-78022dca9da1"},"_deposit":{"created_by":18,"id":"50121","owners":[18],"pid":{"revision_id":0,"type":"depid","value":"50121"},"status":"published"},"_oai":{"id":"oai:kanazawa-u.repo.nii.ac.jp:00050121","sets":["2812:2813:2822"]},"author_link":["90773","90774"],"item_9_biblio_info_8":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2012-05-15","bibliographicIssueDateType":"Issued"},"bibliographicPageStart":"5p.","bibliographicVolumeNumber":"2009-2011","bibliographic_titles":[{"bibliographic_title":"平成23(2011)年度 科学研究費補助金 基盤研究(C) 研究成果報告書"},{"bibliographic_title":"2011 Fiscal Year Final Research Report","bibliographic_titleLang":"en"}]}]},"item_9_creator_33":{"attribute_name":"著者別表示","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{}],"nameIdentifiers":[{},{}]}]},"item_9_description_21":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"ブレインコンピュータインタフェイス(BCI)において,多チャネルで測定された脳波をチャネル間で直交化することにより脳波の特徴を強調する方法を提案した.並列構成された複数の階層形ニューラルネットワーク(MLNN)を用いてメンタルタスク(MT)を分類し,それらの結果を統合する方法により, MTの分類性能が大幅に向上した.他の方式として,脳波の特徴を強調する部分空間フィルタと複数の2分類器,その出力を誤差訂正符号化する方式を提案し,高い分類性能を得た.","subitem_description_type":"Abstract"},{"subitem_description":"Brain Computer Interface(BCI) system has been developed. A method to emphasize features of the brain waves has been proposed. The orthogonalized components and parallel multi-layer neural networks are used to classify themental tasks. These results are averaged to obtain the final result. The high performance for mental task classification has been obtained. Another method, combining the special filter, binary classifiers and error correcting code, has beenproposed, resulting in high performance.","subitem_description_type":"Abstract"}]},"item_9_description_22":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"研究課題/領域番号:21560393, 研究期間(年度):2009-2011","subitem_description_type":"Other"},{"subitem_description":"出典：研究課題「チャネル間直交成分解析と高汎化ニューラルネットワークによるBCIの開発」課題番号21560393\n（KAKEN：科学研究費助成事業データベース（国立情報学研究所）） \n（https://kaken.nii.ac.jp/report/KAKENHI-PROJECT-21560393/21560393seika/）を加工して作成","subitem_description_type":"Other"}]},"item_9_description_5":{"attribute_name":"提供者所属","attribute_value_mlt":[{"subitem_description":"金沢大学理工研究域電子情報通信学系","subitem_description_type":"Other"}]},"item_9_identifier_registration":{"attribute_name":"ID登録","attribute_value_mlt":[{"subitem_identifier_reg_text":"10.24517/00056433","subitem_identifier_reg_type":"JaLC"}]},"item_9_relation_28":{"attribute_name":"関連URI","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_text":"https://kaken.nii.ac.jp/search/?qm=00207945"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://kaken.nii.ac.jp/search/?qm=00207945","subitem_relation_type_select":"URI"}},{"subitem_relation_name":[{"subitem_relation_name_text":"https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-21560393/"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-21560393/","subitem_relation_type_select":"URI"}},{"subitem_relation_name":[{"subitem_relation_name_text":"https://kaken.nii.ac.jp/report/KAKENHI-PROJECT-21560393/21560393seika/"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://kaken.nii.ac.jp/report/KAKENHI-PROJECT-21560393/21560393seika/","subitem_relation_type_select":"URI"}}]},"item_9_version_type_25":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-12-06"}],"displaytype":"detail","filename":"TE-PR-NAKAYAMA-K-kaken 2012-5p.pdf","filesize":[{"value":"263.1 kB"}],"format":"application/pdf","licensetype":"license_11","mimetype":"application/pdf","url":{"label":"TE-PR-NAKAYAMA-K-kaken 2012-5p.pdf","url":"https://kanazawa-u.repo.nii.ac.jp/record/50121/files/TE-PR-NAKAYAMA-K-kaken 2012-5p.pdf"},"version_id":"5ef5113b-2046-4f65-a6cd-0210968cbefb"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"research report","resourceuri":"http://purl.org/coar/resource_type/c_18ws"}]},"item_title":"チャネル間直交成分解析と高汎化ニューラルネットワークによるBCIの開発","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"チャネル間直交成分解析と高汎化ニューラルネットワークによるBCIの開発"},{"subitem_title":"Research of BCI system based on neural networks with high generalization and multi-channel orthogonal components","subitem_title_language":"en"}]},"item_type_id":"9","owner":"18","path":["2822"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-12-06"},"publish_date":"2019-12-06","publish_status":"0","recid":"50121","relation_version_is_last":true,"title":["チャネル間直交成分解析と高汎化ニューラルネットワークによるBCIの開発"],"weko_creator_id":"18","weko_shared_id":-1},"updated":"2023-07-27T13:24:34.359939+00:00"}