{"created":"2025-01-19T01:17:07.893703+00:00","updated":"2025-01-19T15:47:44.688502+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00216607","sets":["1164:5159:10869:10870"]},"path":["10870"],"owner":"44499","recid":"216607","title":["局所性を考慮した一般化グラフ信号サンプリング"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-02-22"},"_buckets":{"deposit":"42926fac-75e3-4ac2-a2a8-01f5b151202a"},"_deposit":{"id":"216607","pid":{"type":"depid","value":"216607","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"局所性を考慮した一般化グラフ信号サンプリング","author_link":["559213","559215","559214","559216"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"局所性を考慮した一般化グラフ信号サンプリング"},{"subitem_title":"A Locally Constrained Sampling Strategy for Generalized Graph Signal Sampling","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ポスターセッション1 ","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-02-22","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京工業大学情報理工学院"},{"subitem_text_value":"東京工業大学情報理工学院"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"School of Computing, Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"School of Computing, Tokyo Institute of Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/216607/files/IPSJ-SLP22140006.pdf","label":"IPSJ-SLP22140006.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLP22140006.pdf","filesize":[{"value":"2.0 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"22"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"5e21428e-c87c-4474-8d8c-6bed40d3b4f2","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"朝倉, 一希"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小野, 峻佑"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kazuki, Asakura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shunsuke, Ono","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10442647","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8663","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本稿では，完全な復元を保証する，サンプルの局所性を考慮したグラフ信号サンプリングの設計手法を提案する．一般化サンプリングに基づく既存の設計手法は復元性能において優れているが，グラフ上で遠い頂点の信号値の加重和をサンプルとする可能性がある．本研究では，頂点領域サンプリングとして機能するサンプリング行列を得る手法を提案する．グラフラプラシアンの多項式で表現されるフィルタを利用することで，サンプルがまたがるホップ数を制限することができる．これにより，大規模なグラフにおけるサンプリングを局所化できる．頂点領域でのサンプリング集合の選択を制約付き凸最適化問題として定式化し，主-双対近接分離法を利用して求解した．実験結果から，提案手法によって復元性能を維持したまま局所性を考慮したサンプルが得られることが示された．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"We propose a design method of vertex domain sampling for graph signals that guarantees perfect reconstruction. The existing method based on generalized graph sampling theory assumes only the sparsity of sampling matrices. We consider obtaining the sampling matrix as vertex domain sampling using filters with the locality. In this setting, obtained samples are combinations of signal values within a limited number of hops. It means that sampling in large graphs can be partitioned into localized problems. We formulate an optimization problem for designing selection matrices under the assumption that the graph filter is given. In the experiments, our method presents localized samples without compromising performance.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告音声言語情報処理（SLP）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-02-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"6","bibliographicVolumeNumber":"2022-SLP-140"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":216607,"links":{}}