{"id":"https://openalex.org/W4400314725","doi":"https://doi.org/10.1109/tsp.2024.3423432","title":"A Generalization of the Convolution Theorem and Its Connections to Non-Stationarity and the Graph Frequency Domain","display_name":"A Generalization of the Convolution Theorem and Its Connections to Non-Stationarity and the Graph Frequency Domain","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400314725","doi":"https://doi.org/10.1109/tsp.2024.3423432"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2024.3423432","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tsp.2024.3423432","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","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/A5076483697","display_name":"Alberto Natali","orcid":"https://orcid.org/0000-0003-0441-7711"},"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":"Alberto Natali","raw_affiliation_strings":["Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering, Mathematics and Computer Science, 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, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering, Mathematics and Computer Science, 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/A5076483697"],"corresponding_institution_ids":["https://openalex.org/I98358874"],"apc_list":null,"apc_paid":null,"fwci":1.0851,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78999251,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"72","issue":null,"first_page":"3424","last_page":"3437"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9976999759674072,"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":0.9976000189781189,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6915276646614075},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.6336002349853516},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.586663007736206},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5081901550292969},{"id":"https://openalex.org/keywords/convolution-theorem","display_name":"Convolution theorem","score":0.5068591237068176},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.489498496055603},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43820568919181824},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.39847227931022644},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3644059896469116},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3243599534034729},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.25282716751098633},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.1941160261631012},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1863238513469696},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.15844732522964478},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10193532705307007}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6915276646614075},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.6336002349853516},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.586663007736206},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5081901550292969},{"id":"https://openalex.org/C79587385","wikidata":"https://www.wikidata.org/wiki/Q2638931","display_name":"Convolution theorem","level":5,"score":0.5068591237068176},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.489498496055603},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43820568919181824},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.39847227931022644},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3644059896469116},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3243599534034729},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.25282716751098633},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.1941160261631012},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1863238513469696},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.15844732522964478},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10193532705307007},{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2024.3423432","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tsp.2024.3423432","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","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":29,"referenced_works":["https://openalex.org/W1991252559","https://openalex.org/W2041741035","https://openalex.org/W2101491865","https://openalex.org/W2113638573","https://openalex.org/W2138824526","https://openalex.org/W2151517138","https://openalex.org/W2151948222","https://openalex.org/W2235146554","https://openalex.org/W2299462150","https://openalex.org/W2504507112","https://openalex.org/W2616297073","https://openalex.org/W2919115771","https://openalex.org/W2963738599","https://openalex.org/W2964334030","https://openalex.org/W2966880477","https://openalex.org/W3087572092","https://openalex.org/W3093639681","https://openalex.org/W3134247470","https://openalex.org/W3157727345","https://openalex.org/W3160429182","https://openalex.org/W4256234326","https://openalex.org/W4287264269","https://openalex.org/W4301009075","https://openalex.org/W4323521169","https://openalex.org/W4372338347","https://openalex.org/W4386955353","https://openalex.org/W4390692039","https://openalex.org/W6632100814","https://openalex.org/W6637883433"],"related_works":["https://openalex.org/W4363675452","https://openalex.org/W2293685972","https://openalex.org/W2899125270","https://openalex.org/W2165363605","https://openalex.org/W1997262258","https://openalex.org/W4290189506","https://openalex.org/W4236917868","https://openalex.org/W2267589039","https://openalex.org/W4224987185","https://openalex.org/W1975739358"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,30,89,98],"present":[4],"a":[5,33,40,50,63,70,100],"novel":[6],"convolution":[7,14,35,48],"theorem":[8,15,79],"which":[9,113],"encompasses":[10],"the":[11,23,56,66,77,83,109],"well":[12,21],"known":[13],"in":[16,49,93],"(graph)":[17],"signal":[18],"processing":[19],"as":[20,22,45],"one":[24],"related":[25],"to":[26,107],"time-varying":[27],"filters.":[28],"Specifically,":[29],"show":[31],"how":[32,76],"node-wise":[34,47],"for":[36],"signals":[37],"supported":[38],"on":[39,104,120],"graph":[41],"can":[42],"be":[43],"expressed":[44],"another":[46],"frequency":[51,110],"domain":[52,111],"graph,":[53,112],"different":[54],"from":[55],"original":[57],"graph.":[58],"This":[59],"is":[60,80,114],"achieved":[61],"through":[62],"parameterization":[64],"of":[65,87,95],"filter":[67],"coefficients":[68],"following":[69],"basis":[71],"expansion":[72],"model.":[73],"After":[74],"showing":[75],"presented":[78],"consistent":[81],"with":[82],"already":[84],"existing":[85],"body":[86],"literature,":[88],"discuss":[90],"its":[91],"implications":[92],"terms":[94],"non-stationarity.":[96],"Finally,":[97],"propose":[99],"data-driven":[101],"algorithm":[102],"based":[103],"subspace":[105],"fitting":[106],"learn":[108],"then":[115],"corroborated":[116],"by":[117],"experimental":[118],"results":[119],"synthetic":[121],"and":[122],"real":[123],"data.":[124]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
