{"created":"2023-06-19T11:37:36.278688+00:00","id":4975,"links":{},"metadata":{"_buckets":{"deposit":"637b4928-785d-4de6-9f24-8fbf78d00cca"},"_deposit":{"created_by":13,"id":"4975","owners":[13],"pid":{"revision_id":0,"type":"depid","value":"4975"},"status":"published"},"_oai":{"id":"oai:mie-u.repo.nii.ac.jp:00004975","sets":["366:367:368:387"]},"author_link":["35375"],"item_4_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1994-12-21","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"143","bibliographicPageStart":"133","bibliographicVolumeNumber":"19","bibliographic_titles":[{"bibliographic_title":"Research reports of the Faculty of Engineering, Mie University"}]}]},"item_4_description_14":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_4_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"A sigmoid function has been utilized for the input/output functions of the back-propagation type neural networks. It, however, has a local minimum problem ; if the output of the sigmoid function becomes 0 or 1, no further learning  occurs even if there are errors between teaching inputs and outputs of the output unit. The offset method of applying some offset values to the intermediate layer cells is thought to be effective in solving the local minimum problem. In this paper, we propose two formulations of offset function ; the linearly decremental offset function that decrements offset values as iteration of the learning process increases, and the logarithmic error offset function that various offset values according as logarithm of output errors. The performance of these methods are evaluated by recognition test of handwriting.","subitem_description_type":"Abstract"}]},"item_4_publisher_30":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Faculty of Engineering, Mie University"}]},"item_4_source_id_7":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"0385-6208","subitem_source_identifier_type":"PISSN"}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA00816341","subitem_source_identifier_type":"NCID"}]},"item_4_text_18":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_text_language":"ja","subitem_text_value":"可変オフセット法によるニューラルネット入出力関数の制御"}]},"item_4_text_65":{"attribute_name":"資源タイプ（三重大）","attribute_value_mlt":[{"subitem_text_value":"Departmental Bulletin Paper / 紀要論文"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Uda, Noriyuki","creatorNameLang":"en"},{"creatorName":"宇田, 紀之","creatorNameLang":"ja"}],"nameIdentifiers":[{}]}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Neural networks","subitem_subject_scheme":"Other"},{"subitem_subject":"Back-propagation","subitem_subject_scheme":"Other"},{"subitem_subject":"Learning algorithm","subitem_subject_scheme":"Other"},{"subitem_subject":"Offset values","subitem_subject_scheme":"Other"},{"subitem_subject":"Recofnition of handwriting","subitem_subject_scheme":"Other"},{"subitem_subject":"Local minimum problem","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Controlling the Input/Output Function of the Neural Network by Variable Offset Rule","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Controlling the Input/Output Function of the Neural Network by Variable Offset Rule","subitem_title_language":"en"}]},"item_type_id":"4","owner":"13","path":["387"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2018-03-15"},"publish_date":"2018-03-15","publish_status":"0","recid":"4975","relation_version_is_last":true,"title":["Controlling the Input/Output Function of the Neural Network by Variable Offset Rule"],"weko_creator_id":"13","weko_shared_id":-1},"updated":"2023-10-05T06:25:19.802052+00:00"}