{"id":"https://openalex.org/W2285079576","doi":"https://doi.org/10.1109/lsp.2016.2514490","title":"Near Orthogonal Oversampled Graph Filter Banks","display_name":"Near Orthogonal Oversampled Graph Filter Banks","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2285079576","doi":"https://doi.org/10.1109/lsp.2016.2514490","mag":"2285079576"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2016.2514490","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2016.2514490","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074687233","display_name":"D.B.H. Tay","orcid":"https://orcid.org/0000-0001-5285-7426"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"David Tay","raw_affiliation_strings":["Department of Engineering, LaTrobe University, Bundoora, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Engineering, LaTrobe University, Bundoora, VIC, Australia","institution_ids":["https://openalex.org/I196829312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007311789","display_name":"Yuichi Tanaka","orcid":"https://orcid.org/0000-0003-4010-3154"},"institutions":[{"id":"https://openalex.org/I92614990","display_name":"Tokyo University of Agriculture and Technology","ror":"https://ror.org/00qg0kr10","country_code":"JP","type":"education","lineage":["https://openalex.org/I92614990"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuichi Tanaka","raw_affiliation_strings":["Graduate School of BASE, Tokyo University of Agriculture and Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of BASE, Tokyo University of Agriculture and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I92614990"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054993189","display_name":"Akie Sakiyama","orcid":null},"institutions":[{"id":"https://openalex.org/I92614990","display_name":"Tokyo University of Agriculture and Technology","ror":"https://ror.org/00qg0kr10","country_code":"JP","type":"education","lineage":["https://openalex.org/I92614990"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akie Sakiyama","raw_affiliation_strings":["Graduate School of BASE, Tokyo University of Agriculture and Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of BASE, Tokyo University of Agriculture and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I92614990"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074687233"],"corresponding_institution_ids":["https://openalex.org/I196829312"],"apc_list":null,"apc_paid":null,"fwci":3.0921,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.92721226,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9761999845504761,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9286999702453613,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/orthogonality","display_name":"Orthogonality","score":0.7000440359115601},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6642864346504211},{"id":"https://openalex.org/keywords/filter-bank","display_name":"Filter bank","score":0.6216831207275391},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5141556262969971},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.45765364170074463},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.4063725471496582},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3205547332763672},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.23497378826141357}],"concepts":[{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.7000440359115601},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6642864346504211},{"id":"https://openalex.org/C100515483","wikidata":"https://www.wikidata.org/wiki/Q3268235","display_name":"Filter bank","level":3,"score":0.6216831207275391},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5141556262969971},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.45765364170074463},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.4063725471496582},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3205547332763672},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.23497378826141357},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2016.2514490","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2016.2514490","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:dro.deakin.edu.au:DU:30107535","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402457","display_name":"Deakin Research Online (Deakin University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149704539","host_organization_name":"Deakin University","host_organization_lineage":["https://openalex.org/I149704539"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W757675842","https://openalex.org/W1481646516","https://openalex.org/W1658679052","https://openalex.org/W1990488619","https://openalex.org/W2004559848","https://openalex.org/W2024496749","https://openalex.org/W2027579212","https://openalex.org/W2035072927","https://openalex.org/W2046275336","https://openalex.org/W2049220509","https://openalex.org/W2101491865","https://openalex.org/W2101789093","https://openalex.org/W2120121938","https://openalex.org/W2158787690","https://openalex.org/W2165837424","https://openalex.org/W2166370383","https://openalex.org/W2185199324","https://openalex.org/W4210770595","https://openalex.org/W4255272544","https://openalex.org/W6622281769","https://openalex.org/W6684366375"],"related_works":["https://openalex.org/W2059318893","https://openalex.org/W2095582735","https://openalex.org/W1965698851","https://openalex.org/W834942123","https://openalex.org/W4232542516","https://openalex.org/W3176637561","https://openalex.org/W1587967017","https://openalex.org/W1967331680","https://openalex.org/W130629949","https://openalex.org/W2993249520"],"abstract_inverted_index":{"A":[0,78],"framework":[1,46],"for":[2,6],"oversampled":[3,22],"filter":[4,23,35],"banks":[5],"graph":[7],"signals":[8],"was":[9,18],"recently":[10],"proposed":[11,124],"by":[12],"Tanaka":[13],"and":[14,49],"Sakiyama":[15],"(2014).":[16],"It":[17],"shown":[19],"that":[20,59,114],"M-channel":[21],"bank":[24],"which":[25,63,83],"is":[26,29,39,60,88,99],"exactly":[27],"orthogonal":[28,62,117],"not":[30],"possible":[31],"with":[32,110],"polynomial":[33],"spectral":[34,97,112],"functions.":[36,108],"The":[37,93],"result":[38],"an":[40,103],"extension":[41],"of":[42,47,67,80,95,105],"the":[43,65,85,96,106,123],"critically":[44],"sampled":[45],"Narang":[48],"Ortega":[50],"(2012).":[51],"In":[52],"this":[53],"work":[54],"we":[55],"present":[56],"a":[57,69],"solution":[58],"nearly":[61,70,74,116],"has":[64],"advantage":[66],"giving":[68],"tight":[71],"transform,":[72],"i.e.":[73],"equal":[75],"frame":[76],"bounds.":[77],"family":[79],"target":[81,107],"functions":[82],"satisfy":[84],"orthogonality":[86],"condition":[87],"constructed":[89],"using":[90,122],"Bernstein":[91],"polynomials.":[92],"design":[94],"filters":[98],"easily":[100,120],"achieved":[101],"through":[102],"approximation":[104],"Filters":[109],"good":[111],"characteristics":[113],"are":[115],"can":[118],"be":[119],"obtained":[121],"method.":[125]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}