{"created":"2025-01-19T01:15:49.571009+00:00","updated":"2025-01-19T16:20:52.414929+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00215041","sets":["6504:10735:10808"]},"path":["10808"],"owner":"44499","recid":"215041","title":["スパイキングニューラルネットワークのための適応型重み減衰を取り入れた教師ありSTDP学習"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-04"},"_buckets":{"deposit":"75ff67a8-6e48-4f05-bfb4-0f07c17c55e0"},"_deposit":{"id":"215041","pid":{"type":"depid","value":"215041","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"スパイキングニューラルネットワークのための適応型重み減衰を取り入れた教師ありSTDP学習","author_link":["553469","553468"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"スパイキングニューラルネットワークのための適応型重み減衰を取り入れた教師ありSTDP学習"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2021-03-04","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"山梨大"},{"subitem_text_value":"山梨大"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/215041/files/IPSJ-Z83-4R-05.pdf","label":"IPSJ-Z83-4R-05.pdf"},"date":[{"dateType":"Available","dateValue":"2021-12-28"}],"format":"application/pdf","filename":"IPSJ-Z83-4R-05.pdf","filesize":[{"value":"1.2 MB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"36871649-f8d9-4f6e-983d-cbbc51729fd9","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"荒木, 裕史"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"服部, 元信"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年,人工知能分野においてスパイキングニューラルネットワーク(SNN)と呼ばれる,新たなニューラルネットワークモデルの研究が盛んになってきている.SNNは脳神経活動を精緻に模倣したモデルであり,工学的研究に留まらず,神経科学分野などにおいても重宝されているモデルである.現存のSNNモデルは特定タスクのおいて優れた性能を獲得できているが,学習の効率性面で改善の余地がある.本研究では,SNNのための効率性を重視した新たな教師あり学習法を提案する.本提案手法により,小さなモデルであっても優れた性能を獲得できるだけでなく,学習の順序を考慮しない,即ち破局的忘却が生じないモデルの構築を可能とする.","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"484","bibliographic_titles":[{"bibliographic_title":"第83回全国大会講演論文集"}],"bibliographicPageStart":"483","bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":215041,"links":{}}