{"id":"https://openalex.org/W2766459737","doi":"https://doi.org/10.23919/eusipco.2017.8081230","title":"Signal processing on kernel-based random graphs","display_name":"Signal processing on kernel-based random graphs","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2766459737","doi":"https://doi.org/10.23919/eusipco.2017.8081230","mag":"2766459737"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2017.8081230","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2017.8081230","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-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/A5017601305","display_name":"Matthew W. Morency","orcid":"https://orcid.org/0000-0001-7642-2427"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Matthew W. Morency","raw_affiliation_strings":["Faculty of Electrical Engineering, Delft University of Technology, Delft, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering, Delft University of Technology, Delft, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089101522","display_name":"Geert Leus","orcid":"https://orcid.org/0000-0001-8288-867X"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Geert Leus","raw_affiliation_strings":["Faculty of Electrical Engineering, Delft University of Technology, Delft, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering, Delft University of Technology, Delft, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017601305"],"corresponding_institution_ids":["https://openalex.org/I98358874"],"apc_list":null,"apc_paid":null,"fwci":1.8706,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.89488985,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"365","last_page":"369"},"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":0.9997000098228455,"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/T11476","display_name":"Graph theory and applications","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/random-graph","display_name":"Random graph","score":0.5618372559547424},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.5016224384307861},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45832765102386475},{"id":"https://openalex.org/keywords/integral-graph","display_name":"Integral graph","score":0.4262201488018036},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.4202965795993805},{"id":"https://openalex.org/keywords/spectral-graph-theory","display_name":"Spectral graph theory","score":0.4142625629901886},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3729199171066284},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.362634539604187},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.34683895111083984},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.3061797022819519},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.2686975598335266},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.13043224811553955}],"concepts":[{"id":"https://openalex.org/C47458327","wikidata":"https://www.wikidata.org/wiki/Q910404","display_name":"Random graph","level":3,"score":0.5618372559547424},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.5016224384307861},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45832765102386475},{"id":"https://openalex.org/C204710682","wikidata":"https://www.wikidata.org/wiki/Q3036983","display_name":"Integral graph","level":5,"score":0.4262201488018036},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.4202965795993805},{"id":"https://openalex.org/C74003402","wikidata":"https://www.wikidata.org/wiki/Q3180727","display_name":"Spectral graph theory","level":5,"score":0.4142625629901886},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3729199171066284},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.362634539604187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.34683895111083984},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.3061797022819519},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.2686975598335266},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.13043224811553955}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2017.8081230","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2017.8081230","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W273178449","https://openalex.org/W1512190194","https://openalex.org/W1566041582","https://openalex.org/W1980573399","https://openalex.org/W1991252559","https://openalex.org/W2016987856","https://openalex.org/W2081632029","https://openalex.org/W2082734581","https://openalex.org/W2101491865","https://openalex.org/W2102907934","https://openalex.org/W2111714602","https://openalex.org/W2111754130","https://openalex.org/W2124637492","https://openalex.org/W2126296671","https://openalex.org/W2138359578","https://openalex.org/W2182708456","https://openalex.org/W2950201802","https://openalex.org/W2950850272","https://openalex.org/W2952817960","https://openalex.org/W3008660429","https://openalex.org/W3102963639","https://openalex.org/W4211076975","https://openalex.org/W6654663854","https://openalex.org/W6676520976"],"related_works":["https://openalex.org/W2165755074","https://openalex.org/W2082971831","https://openalex.org/W2323619857","https://openalex.org/W618655101","https://openalex.org/W259034802","https://openalex.org/W4213419526","https://openalex.org/W2389138578","https://openalex.org/W3193236920","https://openalex.org/W3089804773","https://openalex.org/W2389330739"],"abstract_inverted_index":{"We":[0],"present":[1],"the":[2,71,74,79,84,87,90,98],"theory":[3],"of":[4,6,16,60,73,86,89,102,112],"sequences":[5],"random":[7,17,62],"graphs":[8,19,63],"and":[9,33,56,67,100,119],"their":[10,25,30,34],"convergence":[11],"to":[12,22,24],"limit":[13,26,37],"objects.":[14],"Sequences":[15],"dense":[18],"are":[20,39,65,116],"shown":[21],"converge":[23],"objects":[27,38],"in":[28],"both":[29],"structural":[31],"properties":[32],"spectra.":[35],"The":[36,49,110],"bounded":[40],"symmetric":[41],"functions":[42,51],"on":[43,97],"[0,1]":[44],"<sup":[45],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[46],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[47],".":[48],"kernel":[50],"define":[52],"an":[53],"equivalence":[54],"class":[55],"thus":[57],"identify":[58],"collections":[59],"large":[61],"who":[64],"spectrally":[66],"structurally":[68],"equivalent.":[69],"As":[70],"spectrum":[72,88],"graph":[75,80,92,103,114],"shift":[76],"operator":[77],"defines":[78],"Fourier":[81],"transform":[82],"(GFT),":[83],"behavior":[85],"underlying":[91],"has":[93],"a":[94],"great":[95],"impact":[96],"design":[99],"implementation":[101],"signal":[104],"processing":[105],"operators":[106],"such":[107],"as":[108],"filters.":[109],"spectra":[111],"several":[113],"limits":[115],"derived":[117],"analytically":[118],"verified":[120],"with":[121],"numerical":[122],"examples.":[123]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
