{"created":"2023-07-27T06:25:04.628844+00:00","id":8227,"links":{},"metadata":{"_buckets":{"deposit":"22420536-d51b-4de6-91ff-0177f6c9536a"},"_deposit":{"created_by":3,"id":"8227","owners":[3],"pid":{"revision_id":0,"type":"depid","value":"8227"},"status":"published"},"_oai":{"id":"oai:kanazawa-u.repo.nii.ac.jp:00008227","sets":["934:935:936"]},"author_link":["353","11433"],"item_8_biblio_info_8":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1995-11-01","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"605","bibliographicPageStart":"600","bibliographicVolumeNumber":"1","bibliographic_titles":[{"bibliographic_title":"IEEE International Conference on Neural Networks - Conference Proceedings"}]}]},"item_8_description_21":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Signal classification performance using multilayer neural network (MLNN) and the conventional signal processing methods are theoretically compared under the limited observation period and computational load. The signals with N samples are classified based on frequency components. The comparison is carried out based on degree of freedom the signal detection regions in an N-dimensional signal space. As a result, the MLNN has higher degree of freedom, and can provide more flexible performance for classifying the signals than the conventional methods. This analysis is further investigated throught computer simulations. Multi-frequency signals and the real application, a dial tone receiver, are taken into account. As a result, the MLNN can provide much higher accuracy than the conventional signal processing methods.","subitem_description_type":"Abstract"}]},"item_8_description_5":{"attribute_name":"提供者所属","attribute_value_mlt":[{"subitem_description":"金沢大学理工研究域　電子情報学系","subitem_description_type":"Other"}]},"item_8_publisher_17":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"IEEE = Institute of Electrical and Electronics Engineers"}]},"item_8_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1098-7576","subitem_source_identifier_type":"ISSN"}]},"item_8_version_type_25":{"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":"Hara, Kazuyuki"},{"creatorName":"ナカヤマ, ケンジ","creatorNameLang":"ja-Kana"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Nakayama, Kenji"}],"nameIdentifiers":[{},{},{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2017-10-03"}],"displaytype":"detail","filename":"TE-PR-NAKAYAMA-K-600.pdf","filesize":[{"value":"455.3 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"TE-PR-NAKAYAMA-K-600.pdf","url":"https://kanazawa-u.repo.nii.ac.jp/record/8227/files/TE-PR-NAKAYAMA-K-600.pdf"},"version_id":"4a410ba5-326c-4ba8-957e-24b7f1f6ff57"}]},"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":"conference paper","resourceuri":"http://purl.org/coar/resource_type/c_5794"}]},"item_title":"Signal classification based on frequency analysis using multilayer neural network with limited data and computations","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Signal classification based on frequency analysis using multilayer neural network with limited data and computations"}]},"item_type_id":"8","owner":"3","path":["936"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-10-03"},"publish_date":"2017-10-03","publish_status":"0","recid":"8227","relation_version_is_last":true,"title":["Signal classification based on frequency analysis using multilayer neural network with limited data and computations"],"weko_creator_id":"3","weko_shared_id":-1},"updated":"2023-07-28T02:12:14.120871+00:00"}