{"id":"https://openalex.org/W3088447564","doi":"https://doi.org/10.1109/lsp.2020.3025066","title":"Convergence Analysis of Gaussian SPAWN Under High-Order Graphical Models","display_name":"Convergence Analysis of Gaussian SPAWN Under High-Order Graphical Models","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3088447564","doi":"https://doi.org/10.1109/lsp.2020.3025066","mag":"3088447564"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2020.3025066","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.3025066","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/A5100365118","display_name":"Bin Li","orcid":"https://orcid.org/0000-0001-7697-3544"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Li","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7697-3544","affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051859982","display_name":"Nan Wu","orcid":"https://orcid.org/0000-0002-4982-2975"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Wu","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4982-2975","affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.2441,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.50593403,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"27","issue":null,"first_page":"1725","last_page":"1729"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.7724350690841675},{"id":"https://openalex.org/keywords/belief-propagation","display_name":"Belief propagation","score":0.6277927756309509},{"id":"https://openalex.org/keywords/spawn","display_name":"Spawn (biology)","score":0.5888237953186035},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.5321668386459351},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4824288785457611},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.44621074199676514},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41874241828918457},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.41869205236434937},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4120284914970398},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.39843571186065674},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3590438961982727},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3275139331817627},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.2576141953468323},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21549615263938904}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.7724350690841675},{"id":"https://openalex.org/C152948882","wikidata":"https://www.wikidata.org/wiki/Q4060686","display_name":"Belief propagation","level":3,"score":0.6277927756309509},{"id":"https://openalex.org/C17458331","wikidata":"https://www.wikidata.org/wiki/Q935672","display_name":"Spawn (biology)","level":2,"score":0.5888237953186035},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.5321668386459351},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4824288785457611},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.44621074199676514},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41874241828918457},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.41869205236434937},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4120284914970398},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39843571186065674},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3590438961982727},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3275139331817627},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2576141953468323},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21549615263938904},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C505870484","wikidata":"https://www.wikidata.org/wiki/Q180538","display_name":"Fishery","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2020.3025066","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.3025066","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7995076155","display_name":null,"funder_award_id":"61971041","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":19,"referenced_works":["https://openalex.org/W1603765807","https://openalex.org/W1973902799","https://openalex.org/W2003787552","https://openalex.org/W2012197287","https://openalex.org/W2073782198","https://openalex.org/W2098995249","https://openalex.org/W2105077725","https://openalex.org/W2111521164","https://openalex.org/W2118537895","https://openalex.org/W2133194023","https://openalex.org/W2158122241","https://openalex.org/W2295244470","https://openalex.org/W2467524786","https://openalex.org/W2761712819","https://openalex.org/W2933050413","https://openalex.org/W2964195206","https://openalex.org/W2983810220","https://openalex.org/W3103471669","https://openalex.org/W6676628830"],"related_works":["https://openalex.org/W959529772","https://openalex.org/W4297812452","https://openalex.org/W4368755698","https://openalex.org/W2606077302","https://openalex.org/W4388627352","https://openalex.org/W2140575283","https://openalex.org/W3180766726","https://openalex.org/W2962950510","https://openalex.org/W4286382505","https://openalex.org/W2153267847"],"abstract_inverted_index":{"Gaussian":[0,51,54,74,79,98,114,117],"belief":[1,93],"propagation":[2],"(BP)":[3],"is":[4,81,119],"widely":[5],"used":[6],"for":[7,84],"distributed":[8],"inference.":[9],"Its":[10],"computational":[11,36],"complexity,":[12,37],"and":[13,24,32,38,95,110,116],"communication":[14,39],"overhead":[15,40],"depend":[16],"on":[17],"the":[18,76,90,106],"total":[19],"number":[20],"of":[21,50,78,92,113],"messages":[22,67],"updated,":[23],"transmitted":[25],"among":[26],"variable":[27],"nodes,":[28],"respectively.":[29],"For":[30],"large,":[31],"dense":[33],"networks,":[34],"both":[35],"could":[41,62],"be":[42,63],"extremely":[43],"high.":[44],"To":[45],"this":[46],"end,":[47],"a":[48,59,111],"variant":[49],"BP":[52],"called":[53],"SPAWN":[55,80,118],"(sum-product":[56],"algorithm":[57],"over":[58],"wireless":[60],"network)":[61],"applied,":[64],"where":[65],"outgoing":[66],"are":[68,102],"approximated":[69],"by":[70],"beliefs.":[71],"Similar":[72],"to":[73,104],"BP,":[75,115],"convergence":[77,91],"not":[82],"guaranteed":[83],"loopy":[85],"graphs.":[86],"Therefore,":[87],"we":[88],"analyze":[89],"means,":[94],"variances":[96],"in":[97],"SPAWN.":[99],"Numerical":[100],"results":[101],"presented":[103],"corroborate":[105],"newly":[107],"established":[108],"theories":[109],"comparison":[112],"illustrated.":[120]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}