{"id":"https://openalex.org/W7117114424","doi":"https://doi.org/10.1109/tsipn.2025.3648322","title":"Improved Diffusion Recursive Least Squares for Graph Signal Estimation on Distributed Network","display_name":"Improved Diffusion Recursive Least Squares for Graph Signal Estimation on Distributed Network","publication_year":2025,"publication_date":"2025-12-24","ids":{"openalex":"https://openalex.org/W7117114424","doi":"https://doi.org/10.1109/tsipn.2025.3648322"},"language":null,"primary_location":{"id":"doi:10.1109/tsipn.2025.3648322","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2025.3648322","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"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 and Information Processing over Networks","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/A5113534354","display_name":"Yi Xin Hua","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108113","display_name":"Yango University","ror":"https://ror.org/01eqh1863","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210108113"]},{"id":"https://openalex.org/I78978612","display_name":"Yangzhou University","ror":"https://ror.org/03tqb8s11","country_code":"CN","type":"education","lineage":["https://openalex.org/I78978612"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Hua","raw_affiliation_strings":["College Information and Artificial Intelligence, Yangzhou University, Yangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0660-7826","affiliations":[{"raw_affiliation_string":"College Information and Artificial Intelligence, Yangzhou University, Yangzhou, China","institution_ids":["https://openalex.org/I78978612","https://openalex.org/I4210108113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102825275","display_name":"Zhangfa Wu","orcid":"https://orcid.org/0009-0007-3009-9661"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhangfa Wu","raw_affiliation_strings":["School of Electronic Information, Northwestern Polytechnical University, Xi&#x0027;an, China"],"raw_orcid":"https://orcid.org/0009-0007-3009-9661","affiliations":[{"raw_affiliation_string":"School of Electronic Information, Northwestern Polytechnical University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111084155","display_name":"Hongping Gan","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongping Gan","raw_affiliation_strings":["School of Software, Northwestern Polytechnical University, Xi&#x0027;an, China"],"raw_orcid":"https://orcid.org/0000-0002-4853-5077","affiliations":[{"raw_affiliation_string":"School of Software, Northwestern Polytechnical University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113534354"],"corresponding_institution_ids":["https://openalex.org/I4210108113","https://openalex.org/I78978612"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.79880427,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"31","last_page":"41"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9381999969482422,"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":0.9381999969482422,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.02500000037252903,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.0017000000225380063,"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/graph","display_name":"Graph","score":0.6096000075340271},{"id":"https://openalex.org/keywords/recursive-least-squares-filter","display_name":"Recursive least squares filter","score":0.5759999752044678},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5408999919891357},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.4325000047683716},{"id":"https://openalex.org/keywords/graph-bandwidth","display_name":"Graph bandwidth","score":0.41850000619888306},{"id":"https://openalex.org/keywords/distributed-algorithm","display_name":"Distributed algorithm","score":0.37720000743865967},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.3765999972820282},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.3756999969482422},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.37059998512268066}],"concepts":[{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6096000075340271},{"id":"https://openalex.org/C145249878","wikidata":"https://www.wikidata.org/wiki/Q2835868","display_name":"Recursive least squares filter","level":3,"score":0.5759999752044678},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5511000156402588},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5408999919891357},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5358999967575073},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.4325000047683716},{"id":"https://openalex.org/C134727501","wikidata":"https://www.wikidata.org/wiki/Q5597073","display_name":"Graph bandwidth","level":5,"score":0.41850000619888306},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38659998774528503},{"id":"https://openalex.org/C130120984","wikidata":"https://www.wikidata.org/wiki/Q2835898","display_name":"Distributed algorithm","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.3765999972820282},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.3756999969482422},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.37059998512268066},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3562999963760376},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33469998836517334},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.329800009727478},{"id":"https://openalex.org/C76444178","wikidata":"https://www.wikidata.org/wiki/Q72897900","display_name":"Connectivity","level":3,"score":0.32749998569488525},{"id":"https://openalex.org/C32617633","wikidata":"https://www.wikidata.org/wiki/Q1426666","display_name":"Least mean squares filter","level":3,"score":0.31529998779296875},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C38754835","wikidata":"https://www.wikidata.org/wiki/Q2003238","display_name":"Strongly connected component","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.2906999886035919},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C157406716","wikidata":"https://www.wikidata.org/wiki/Q4115842","display_name":"Topological graph theory","level":5,"score":0.2759999930858612},{"id":"https://openalex.org/C166501922","wikidata":"https://www.wikidata.org/wiki/Q1786523","display_name":"Signal-flow graph","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C2776003309","wikidata":"https://www.wikidata.org/wiki/Q1988072","display_name":"Adaptive algorithm","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsipn.2025.3648322","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2025.3648322","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"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 and Information Processing over Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.539341151714325,"display_name":"Partnerships for the goals"}],"awards":[{"id":"https://openalex.org/G6716188234","display_name":null,"funder_award_id":"62471395","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1966992934","https://openalex.org/W2007075102","https://openalex.org/W2016910422","https://openalex.org/W2047565655","https://openalex.org/W2121820607","https://openalex.org/W2520179645","https://openalex.org/W2562582361","https://openalex.org/W2767057771","https://openalex.org/W2796431263","https://openalex.org/W2890187679","https://openalex.org/W3000377637","https://openalex.org/W3032899718","https://openalex.org/W3035497236","https://openalex.org/W3036074714","https://openalex.org/W3036553878","https://openalex.org/W3046404508","https://openalex.org/W3120910141","https://openalex.org/W4226124542","https://openalex.org/W4281258570","https://openalex.org/W4289535463","https://openalex.org/W4295438412","https://openalex.org/W4323644153","https://openalex.org/W4323644189","https://openalex.org/W4362500663","https://openalex.org/W4372347353","https://openalex.org/W4376481087","https://openalex.org/W4376851446","https://openalex.org/W4391097105","https://openalex.org/W4391661613","https://openalex.org/W4396817460","https://openalex.org/W4399767304","https://openalex.org/W4400314725","https://openalex.org/W4400679740"],"related_works":[],"abstract_inverted_index":{"Streaming":[0],"graph":[1,12,78,86,116,144,184,206,225],"signal":[2],"(GS)":[3],"estimation":[4,36,67,213],"is":[5,57,110,127,136,149],"common":[6],"in":[7,34,50],"various":[8],"network":[9],"systems.":[10],"Several":[11],"filter":[13],"algorithms":[14],"have":[15],"been":[16],"proposed":[17,102,156,205],"for":[18],"streaming":[19,113],"GS":[20,114],"estimation,":[21],"but":[22],"they":[23],"still":[24],"fail":[25],"to":[26,69],"reach":[27],"optimal":[28,32],"levels.":[29],"To":[30,73],"achieve":[31,210],"performance":[33,68,175,214],"both":[35,91],"accuracy":[37],"and":[38,83,115,120,138,161,177,199,215,218],"convergence":[39,163,216],"rate,":[40],"this":[41,75],"paper":[42],"adopts":[43],"the":[44,54,66,93,98,123,155,172,179,182,204,211,223],"recursive":[45,63,95,125,134],"least":[46],"squares":[47],"(RLS)":[48],"method":[49],"processing":[51],"GS.":[52],"When":[53],"RLS":[55,79,88],"algorithm":[56,82,148,157,208],"directly":[58],"combined":[59],"with":[60,80,194],"GS,":[61],"its":[62],"mechanism":[64,126,135],"causes":[65,173],"experience":[70],"severe":[71],"degradation.":[72],"address":[74],"issue,":[76],"a":[77,84,131,142,165],"non-cooperation":[81],"distributed":[85,143,183],"diffusion":[87],"(DRLS)":[89],"algorithm,":[90],"following":[92],"fully":[94],"structure":[96],"of":[97,174,181,197],"standard":[99],"RLS,":[100],"are":[101,118],"first.":[103],"By":[104],"analyzing":[105],"these":[106],"two":[107,191],"algorithms,":[108],"it":[109],"found":[111],"that":[112,154,203],"topology":[117],"complex":[119],"variable,":[121],"so":[122],"previous":[124],"not":[128],"suitable.":[129],"Therefore,":[130],"dynamic":[132],"adaptive":[133],"designed,":[137],"based":[139],"on":[140,190],"this,":[141],"improved":[145],"DRLS":[146],"(IDRLS)":[147],"proposed.":[150],"Convergence":[151],"analysis":[152],"confirms":[153],"achieves":[158],"mean":[159],"stability":[160],"mean-square":[162],"at":[164],"linear":[166],"rate.":[167],"Furthermore,":[168],"we":[169],"thoroughly":[170],"examine":[171],"degradation":[176],"demonstrate":[178],"superiority":[180],"IDRLS":[185,207],"algorithm.":[186],"Finally,":[187],"experiments,":[188],"conducted":[189],"different":[192,195],"graphs":[193],"levels":[196],"sparsity":[198],"real-world":[200],"dataset,":[201],"verify":[202],"can":[209],"superior":[212],"rate":[217],"be":[219],"more":[220],"effective":[221],"than":[222],"related":[224],"algorithms.":[226]},"counts_by_year":[],"updated_date":"2026-01-08T20:05:33.558190","created_date":"2025-12-24T00:00:00"}
