{"_buckets": {"deposit": "2e14d049-3d69-46f9-9e03-d800854ee0c5"}, "_deposit": {"created_by": 3, "id": "1264", "owners": [3], "pid": {"revision_id": 0, "type": "depid", "value": "1264"}, "status": "published"}, "_oai": {"id": "oai:ir.kagoshima-u.ac.jp:00001264", "sets": ["36", "5367"]}, "author_link": ["79861", "4261", "79858", "79862", "79856", "79860", "79859", "79857", "4259"], "item_7_alternative_title_19": {"attribute_name": "タイトルよみ", "attribute_value_mlt": [{"subitem_alternative_title": "RBF　ネットワーク　ト　メンエキテキ　アルゴリズム　ニヨル　ヒセンケイ　システム　ノ　オンライン　ドウテイホウ"}]}, "item_7_biblio_info_5": {"attribute_name": "収録雑誌名", "attribute_value_mlt": [{"bibliographicPageEnd": "34", "bibliographicPageStart": "27", "bibliographicVolumeNumber": "47", "bibliographic_titles": [{"bibliographic_title": "鹿児島大学工学部研究報告"}]}]}, "item_7_date_6": {"attribute_name": "作成日", "attribute_value_mlt": [{"subitem_date_issued_datetime": "2005-10-28"}]}, "item_7_description_4": {"attribute_name": "要約(Abstract)", "attribute_value_mlt": [{"subitem_description": "This paper deals with an on-line identification method based on the radial basis function (RBF) network model for continuous-time nonlinear systems. The nonlinear term of the objective system is represented by the RBF network. The immune algorithm (IA) is utilized to track the system parameters and nonlinear term. The objective function for the identification is regarded as the antigen. The candidates of the estimated model are coded into binary bit strings as the antibodies and searched by the IA. 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