{"created":"2023-05-15T14:21:41.809794+00:00","id":3444,"links":{},"metadata":{"_buckets":{"deposit":"1dd8e34c-2de6-4b90-b7d2-36d2731d0cc5"},"_deposit":{"created_by":3,"id":"3444","owners":[3],"pid":{"revision_id":0,"type":"depid","value":"3444"},"status":"published"},"_oai":{"id":"oai:bunkyo.repo.nii.ac.jp:00003444","sets":["1:26:199"]},"author_link":["4424","4425"],"item_5_biblio_info_13":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1994-01-01"},"bibliographicPageEnd":"128","bibliographicPageStart":"97","bibliographicVolumeNumber":"15","bibliographic_titles":[{"bibliographic_title":"情報研究"},{"bibliographic_title":"Information and Communication Studies"}]}]},"item_5_date_43":{"attribute_name":"作成日","attribute_value_mlt":[{"subitem_date_issued_datetime":"2012-01-17"}]},"item_5_description_12":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"　It is presented here that an associative neural-network binary memory system on n-dimensional Euclidean space Rn suggested by K. Nijima is able to be extended to a system on any separable Hilbert space ◆◆ using a corresponding pattern model Tφ of a pattern φ proposed by S. Suzuki. Applying to a problem concerning at how many stages a pattern-recognition process converges practically an iterative scheme suggested by P. Alfeld which can give a solution of a fixed-point equation on Rn, it is shown that the process has a solution of a constrained minimization problem.\n　By virtue of this research, the associative system may act upon unitary-transformation invariances such as rotations, scalings, and translations, etc. or perceptual constancies appearing in the psychology, and a design of its weights and thresholds and a evaluation about a convergence of the associatively recalling process may be precisely shown.\n\\n　可分なHilbert空間◆◆の元としてのパターンφの,S.Suzukiの提案したパターンモデルTφを用いれば,ユークリッド空間.Rnでの新島耕一による\"連想記憶のニューラルネット2値モデル\"が◆◆へと拡張され,然も,RnからRnへの写像に関するPeter Alfeldの \"不動点方程式の解法としてのan iterative scheme\" を適用して,本連想記憶モデルによるパターン認識過程が何段階でほぼ収束するかなどに関し, the constrained minimization problemの解として得られることが示されている。\n　本研究によって,可分なHilbert空間◆◆での連想形記憶ニューラルネットの2値モデルにユニタリ座標変換不変性(rotation, scaling, translation等に対する不変性,あるいは心理学でいう一種の知覚の恒常性)を備えさせることが可能になり,その重み・閾値の設計法,連想過程の収束の評価が精密にできるようになった。","subitem_description_type":"Abstract"}]},"item_5_description_38":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_5_source_id_19":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"03893367"}]},"item_5_text_39":{"attribute_name":"本文言語","attribute_value_mlt":[{"subitem_text_value":"日本語"}]},"item_5_text_42":{"attribute_name":"ID","attribute_value_mlt":[{"subitem_text_value":"BKSJ150009"}]},"item_5_text_7":{"attribute_name":"Author","attribute_value_mlt":[{"subitem_text_value":"Suzuki, Shoichi"},{"subitem_text_value":"Sakuma, Takuya"}]},"item_5_text_8":{"attribute_name":"所属機関","attribute_value_mlt":[{"subitem_text_value":"文教大学情報学部"},{"subitem_text_value":"文教大学情報学部"}]},"item_5_text_9":{"attribute_name":"Institution","attribute_value_mlt":[{"subitem_text_value":"Bunkyo University Faculty of Information and Communications"},{"subitem_text_value":"Bunkyo University Faculty of Information and Communications"}]},"item_5_version_type_35":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"鈴木, 昇一"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐久間, 拓也"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2018-03-24"}],"displaytype":"detail","filename":"BKSJ150009.pdf","filesize":[{"value":"1.3 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"BKSJ150009.pdf","url":"https://bunkyo.repo.nii.ac.jp/record/3444/files/BKSJ150009.pdf"},"version_id":"e61cbb29-74f9-40a7-a3e5-30bb78ee5002"}]},"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":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"パターンモデルを用いた不動点探索形連想記憶システム方程式","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"パターンモデルを用いた不動点探索形連想記憶システム方程式"},{"subitem_title":"An Associative Memory System Equation of Fixed-Point Searching Type Using a Pattern-Model"}]},"item_type_id":"5","owner":"3","path":["199"],"pubdate":{"attribute_name":"公開日","attribute_value":"2012-01-17"},"publish_date":"2012-01-17","publish_status":"0","recid":"3444","relation_version_is_last":true,"title":["パターンモデルを用いた不動点探索形連想記憶システム方程式"],"weko_creator_id":"3","weko_shared_id":-1},"updated":"2023-05-16T14:21:37.737212+00:00"}