{"created":"2023-06-20T15:46:01.342506+00:00","id":513,"links":{},"metadata":{"_buckets":{"deposit":"09e102bb-86b0-4bc7-a590-f47c4dab5831"},"_deposit":{"created_by":4,"id":"513","owners":[4],"pid":{"revision_id":0,"type":"depid","value":"513"},"status":"published"},"_oai":{"id":"oai:hama-med.repo.nii.ac.jp:00000513","sets":["1:11"]},"author_link":["1383","1384","1385","1386"],"item_3_alternative_title_1":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"Transient Change in Discharging Probability of Neurons when the Inputs Operates more than Two Neurons."}]},"item_3_biblio_info_5":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1999-12-11","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"494","bibliographicPageEnd":"140","bibliographicPageStart":"133","bibliographicVolumeNumber":"99","bibliographic_titles":[{"bibliographic_title":"電子情報通信学会技術研究報告. NC, ニューロコンピューティング IEICE technical report. Neurocomputing"}]}]},"item_3_description_9":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"神経細胞群がインパルス処理を行う過渡的過程において標的神経細胞が複数個ある場合の解析法をSaaty (1960)の研究にもとずいて紹介した。入力インパルスは均一かつ独立、無記憶型のポアソン型時系列(平均λ)とした。入力を処理する神経細胞は2個ある場合を解析した。本研究では神経組織の任意の時刻においてすでに1個のインパルスが処理されている(処理確率:μ)確率P1 (t)に関する連立微分差分確率方程式を母関数展開およびラプラス積分変換を用いて解いた。本研究では簡単のため処理する神経は2個とした。P1 (t)は初期条件によって大きく変化した。本研究方法をさらに発展させることで多数の神経細胞が同時に神経情報を処理する場合の時間経過を分析するのに有用である。  We introduced a mathematical method for processing of neural signal where there are more than two neurons. The basic concept derives from the queuing theory of counter proposed by Saaty (1960). The arriving impulses constitutes a Poisson distribution which is characterized by independently and identically distribution with mean of λ. The impulse departure from the processing neuron also constitutes a sequence of independent and identically distribution with mean of μ. For the initial condition, we set that there are iunits preexisting in the system at t = 0. The probabilistic differential-difference equations were solved by generating function technique. The present method will be available for analyzing the simultaneous neural processing system.","subitem_description_type":"Abstract"}]},"item_3_publisher_6":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"電子情報通信学会"}]},"item_3_relation_22":{"attribute_name":"NII論文ID","attribute_value_mlt":[{"subitem_relation_type":"isIdenticalTo","subitem_relation_type_id":{"subitem_relation_type_id_text":"110003234399","subitem_relation_type_select":"NAID"}}]},"item_3_rights_7":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"電子情報通信学会"},{"subitem_rights":"本文データは学協会の許諾に基づきCiNiiから複製したものである"}]},"item_3_source_id_19":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"09135685","subitem_source_identifier_type":"ISSN"}]},"item_3_version_type_32":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"平山, 博史"}],"nameIdentifiers":[{"nameIdentifier":"1383","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"北川, 敬之"}],"nameIdentifiers":[{"nameIdentifier":"1384","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"沖田, 善光"}],"nameIdentifiers":[{"nameIdentifier":"1385","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"数井, 輝久"}],"nameIdentifiers":[{"nameIdentifier":"1386","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2018-08-27"}],"displaytype":"detail","filename":"110003234399.pdf","filesize":[{"value":"548.5 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"110003234399.pdf","url":"https://hama-med.repo.nii.ac.jp/record/513/files/110003234399.pdf"},"version_id":"39c54d2d-fecf-401e-96e8-6259575d2904"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"均一","subitem_subject_scheme":"Other"},{"subitem_subject":"独立","subitem_subject_scheme":"Other"},{"subitem_subject":"無記憶過程","subitem_subject_scheme":"Other"},{"subitem_subject":"ポアソン型時系列","subitem_subject_scheme":"Other"},{"subitem_subject":"神経細胞活動","subitem_subject_scheme":"Other"},{"subitem_subject":"連立微分差分確率方程式","subitem_subject_scheme":"Other"},{"subitem_subject":"Independent Identical Distribution","subitem_subject_scheme":"Other"},{"subitem_subject":"Poisson input","subitem_subject_scheme":"Other"},{"subitem_subject":"Neural processing","subitem_subject_scheme":"Other"},{"subitem_subject":"Generator function","subitem_subject_scheme":"Other"}]},"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":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"入力が複数個の神経細胞に作用する場合の発射確率の過渡的変動","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"入力が複数個の神経細胞に作用する場合の発射確率の過渡的変動","subitem_title_language":"ja"}]},"item_type_id":"3","owner":"4","path":["11"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2013-08-27"},"publish_date":"2013-08-27","publish_status":"0","recid":"513","relation_version_is_last":true,"title":["入力が複数個の神経細胞に作用する場合の発射確率の過渡的変動"],"weko_creator_id":"4","weko_shared_id":-1},"updated":"2023-08-02T05:44:43.760486+00:00"}