{"id":"https://openalex.org/W4392851344","doi":"https://doi.org/10.1186/s13634-024-01133-3","title":"An efficient algorithm with fast convergence rate for sparse graph signal reconstruction","display_name":"An efficient algorithm with fast convergence rate for sparse graph signal reconstruction","publication_year":2024,"publication_date":"2024-03-15","ids":{"openalex":"https://openalex.org/W4392851344","doi":"https://doi.org/10.1186/s13634-024-01133-3"},"language":"en","primary_location":{"id":"doi:10.1186/s13634-024-01133-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-024-01133-3","pdf_url":null,"source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1110-8657","issn":["1110-8657","1687-0433","1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1186/s13634-024-01133-3","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073573930","display_name":"Yuting Cao","orcid":"https://orcid.org/0009-0006-7660-1779"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuting Cao","raw_affiliation_strings":["School of Information Science and Technolog, Donghua University, Shanghai, 201620, China"],"raw_orcid":"https://orcid.org/0009-0006-7660-1779","affiliations":[{"raw_affiliation_string":"School of Information Science and Technolog, Donghua University, Shanghai, 201620, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061105504","display_name":"Xueqin Jiang","orcid":"https://orcid.org/0000-0002-0414-4349"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xue-Qin Jiang","raw_affiliation_strings":["School of Information Science and Technolog, Donghua University, Shanghai, 201620, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technolog, Donghua University, Shanghai, 201620, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100370463","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0002-5421-5678"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["School of Data Science, Fudan University, Shanghai, 200433, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University, Shanghai, 200433, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101523028","display_name":"Shubo Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shubo Zhou","raw_affiliation_strings":["School of Information Science and Technolog, Donghua University, Shanghai, 201620, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technolog, Donghua University, Shanghai, 201620, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086796043","display_name":"Xinxin Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinxin Hou","raw_affiliation_strings":["School of Information Science and Technolog, Donghua University, Shanghai, 201620, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technolog, Donghua University, Shanghai, 201620, China","institution_ids":["https://openalex.org/I181326427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5061105504"],"corresponding_institution_ids":["https://openalex.org/I181326427"],"apc_list":{"value":1790,"currency":"USD","value_usd":1790},"apc_paid":{"value":1790,"currency":"USD","value_usd":1790},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02863415,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2024","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.7384315133094788},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6226302981376648},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5708099007606506},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.520257830619812},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5034014582633972},{"id":"https://openalex.org/keywords/graph-bandwidth","display_name":"Graph bandwidth","score":0.4929535388946533},{"id":"https://openalex.org/keywords/dense-graph","display_name":"Dense graph","score":0.46395984292030334},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.32051175832748413},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.23647868633270264},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.20940998196601868},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.1377955675125122}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.7384315133094788},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6226302981376648},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5708099007606506},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.520257830619812},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5034014582633972},{"id":"https://openalex.org/C134727501","wikidata":"https://www.wikidata.org/wiki/Q5597073","display_name":"Graph bandwidth","level":5,"score":0.4929535388946533},{"id":"https://openalex.org/C13251829","wikidata":"https://www.wikidata.org/wiki/Q3085841","display_name":"Dense graph","level":5,"score":0.46395984292030334},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.32051175832748413},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.23647868633270264},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.20940998196601868},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.1377955675125122},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C102192266","wikidata":"https://www.wikidata.org/wiki/Q4545823","display_name":"1-planar graph","level":4,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s13634-024-01133-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-024-01133-3","pdf_url":null,"source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1110-8657","issn":["1110-8657","1687-0433","1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3f4f157972bb4f5caac3eec7e3b28ac7","is_oa":false,"landing_page_url":"https://doaj.org/article/3f4f157972bb4f5caac3eec7e3b28ac7","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-23 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s13634-024-01133-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-024-01133-3","pdf_url":null,"source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1110-8657","issn":["1110-8657","1687-0433","1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1540550726","https://openalex.org/W1971368490","https://openalex.org/W2030368230","https://openalex.org/W2051386052","https://openalex.org/W2065321782","https://openalex.org/W2095414057","https://openalex.org/W2101491865","https://openalex.org/W2116148865","https://openalex.org/W2127271355","https://openalex.org/W2129638195","https://openalex.org/W2160979406","https://openalex.org/W2235146554","https://openalex.org/W2289917018","https://openalex.org/W2796431263","https://openalex.org/W2891091350","https://openalex.org/W2949089139","https://openalex.org/W2961495769","https://openalex.org/W2963322354","https://openalex.org/W2963444162","https://openalex.org/W2963521934","https://openalex.org/W2963846176","https://openalex.org/W2965270526","https://openalex.org/W2970633157","https://openalex.org/W2992741647","https://openalex.org/W2998553334","https://openalex.org/W3008709738","https://openalex.org/W3205345709","https://openalex.org/W3215638086","https://openalex.org/W4223905980","https://openalex.org/W4250955649","https://openalex.org/W4287783394","https://openalex.org/W4289656310","https://openalex.org/W4298446196","https://openalex.org/W4300796748","https://openalex.org/W4312036194","https://openalex.org/W4361186083"],"related_works":["https://openalex.org/W2378166785","https://openalex.org/W2156466545","https://openalex.org/W2379468505","https://openalex.org/W3104324607","https://openalex.org/W4206981968","https://openalex.org/W1987102304","https://openalex.org/W2601968125","https://openalex.org/W2308961925","https://openalex.org/W4285251805","https://openalex.org/W2102910599"],"abstract_inverted_index":{"Abstract":[0],"In":[1,112],"this":[2],"paper,":[3],"we":[4,81,101],"consider":[5],"the":[6,12,32,42,54,63,84,88,96,104,108,113,127,130,136],"graph":[7,13,29,33,56,67],"signals":[8,30],"are":[9],"sparse":[10,28,66],"in":[11,31],"Fourier":[14,34],"domain":[15],"and":[16],"propose":[17],"an":[18],"iterative":[19],"threshold":[20,49,73,89],"compressed":[21,44],"sensing":[22,45],"reconstruction":[23,52,69],"(ITCSR)":[24],"algorithm":[25,39,61,133],"to":[26,75,135],"reconstruct":[27],"domain.":[35],"The":[36,58],"proposed":[37,59,109,131],"ITCSR":[38,60,110,132],"derives":[40],"from":[41],"well-known":[43],"by":[46,70,94],"considering":[47],"a":[48,72,77],"for":[50,87],"sparsity-promoting":[51],"of":[53,65,107,129],"underlying":[55],"signals.":[57],"enhances":[62],"performance":[64],"signal":[68],"introducing":[71],"function":[74],"determine":[76],"suitable":[78,85],"threshold.":[79],"Furthermore,":[80],"demonstrate":[82,126],"that":[83],"parameters":[86],"can":[90],"be":[91],"automatically":[92],"determined":[93],"leveraging":[95],"sparrow":[97],"search":[98],"algorithm.":[99,111],"Moreover,":[100],"analytically":[102],"prove":[103],"convergence":[105],"property":[106],"experimental,":[114],"numerical":[115],"tests":[116],"with":[117],"synthetic":[118],"as":[119,121],"well":[120],"3D":[122],"point":[123],"cloud":[124],"data":[125],"merits":[128],"relative":[134],"baseline":[137],"algorithms.":[138]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}