{"id":"https://openalex.org/W2101374845","doi":"https://doi.org/10.1109/tsp.2011.2140106","title":"Sparse Variational Bayesian SAGE Algorithm With Application to the Estimation of Multipath Wireless Channels","display_name":"Sparse Variational Bayesian SAGE Algorithm With Application to the Estimation of Multipath Wireless Channels","publication_year":2011,"publication_date":"2011-04-08","ids":{"openalex":"https://openalex.org/W2101374845","doi":"https://doi.org/10.1109/tsp.2011.2140106","mag":"2101374845"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2011.2140106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2011.2140106","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":true,"oa_status":"green","oa_url":"https://vbn.aau.dk/ws/files/61155739/Sparse_Variational_Bayesian_SAGE_Algorithm.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047628893","display_name":"Dmitriy Shutin","orcid":"https://orcid.org/0000-0002-6065-6453"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"D. Shutin","raw_affiliation_strings":["Department of Electrical Engineering, Princeton University, Princeton, NJ, USA","Dept. of Electr. Eng., Princeton Univ., Princeton, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Princeton University, Princeton, NJ, USA","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Princeton Univ., Princeton, NJ, USA","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064657299","display_name":"Bernard H. Fleury","orcid":"https://orcid.org/0000-0002-9061-3083"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"B. H. Fleury","raw_affiliation_strings":["Section Navigation and Communications, Department of Electronic Systems, University of Aalborg, Aalborg, Denmark","[Dept. of Electron. Syst., Aalborg Univ., Aalborg, Denmark]"],"affiliations":[{"raw_affiliation_string":"Section Navigation and Communications, Department of Electronic Systems, University of Aalborg, Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]},{"raw_affiliation_string":"[Dept. of Electron. Syst., Aalborg Univ., Aalborg, Denmark]","institution_ids":["https://openalex.org/I891191580"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5047628893"],"corresponding_institution_ids":["https://openalex.org/I20089843"],"apc_list":null,"apc_paid":null,"fwci":7.4869,"has_fulltext":true,"cited_by_count":99,"citation_normalized_percentile":{"value":0.97989459,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"59","issue":"8","first_page":"3609","last_page":"3623"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.996399998664856,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9936000108718872,"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/multipath-propagation","display_name":"Multipath propagation","score":0.669514000415802},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6278437972068787},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.562917172908783},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5581169724464417},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.4164969325065613},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4102790355682373},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.37335002422332764},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33168986439704895},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3271287977695465},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.2511245608329773},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1661299765110016},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08690783381462097},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07692411541938782}],"concepts":[{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.669514000415802},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6278437972068787},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.562917172908783},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5581169724464417},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.4164969325065613},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4102790355682373},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.37335002422332764},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33168986439704895},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3271287977695465},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2511245608329773},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1661299765110016},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08690783381462097},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07692411541938782},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2011.2140106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2011.2140106","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"},{"id":"pmh:oai:pure.atira.dk:openaire/a169caef-004d-4a52-af04-d09a241af9c3","is_oa":true,"landing_page_url":"https://vbn.aau.dk/da/publications/a169caef-004d-4a52-af04-d09a241af9c3","pdf_url":"https://vbn.aau.dk/ws/files/61155739/Sparse_Variational_Bayesian_SAGE_Algorithm.pdf","source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Shutin, D & Fleury, B H 2011, 'Sparse Variational Bayesian SAGE Algorithm With Application to the Estimation of Multipath Wireless Channels', I E E E Transactions on Signal Processing, vol. 59, no. 8, pp. 3609-3623. https://doi.org/10.1109/TSP.2011.2140106","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:openaire/a169caef-004d-4a52-af04-d09a241af9c3","is_oa":true,"landing_page_url":"https://vbn.aau.dk/da/publications/a169caef-004d-4a52-af04-d09a241af9c3","pdf_url":"https://vbn.aau.dk/ws/files/61155739/Sparse_Variational_Bayesian_SAGE_Algorithm.pdf","source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Shutin, D & Fleury, B H 2011, 'Sparse Variational Bayesian SAGE Algorithm With Application to the Estimation of Multipath Wireless Channels', I E E E Transactions on Signal Processing, vol. 59, no. 8, pp. 3609-3623. https://doi.org/10.1109/TSP.2011.2140106","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[{"score":0.8600000143051147,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G1771759570","display_name":null,"funder_award_id":"ICT-248894","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G2447788411","display_name":null,"funder_award_id":"unknown","funder_id":"https://openalex.org/F4320321181","funder_display_name":"Austrian Science Fund"},{"id":"https://openalex.org/G29158806","display_name":null,"funder_award_id":"216715","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G3311625613","display_name":null,"funder_award_id":"ICT-217033","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G4447653093","display_name":null,"funder_award_id":"Network","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G5675444185","display_name":"Wireless Hybrid Enhanced Mobile Radio Estimators - Phase 2","funder_award_id":"248894","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G6590085147","display_name":"Wireless Hybrid Enhanced Mobile Radio Estimators","funder_award_id":"217033","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8051717526","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320321181","display_name":"Austrian Science Fund","ror":"https://ror.org/013tf3c58"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2101374845.pdf","grobid_xml":"https://content.openalex.org/works/W2101374845.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W653761051","https://openalex.org/W1506806321","https://openalex.org/W1567512734","https://openalex.org/W1591346633","https://openalex.org/W1607198972","https://openalex.org/W1633751774","https://openalex.org/W1648445109","https://openalex.org/W1977252496","https://openalex.org/W1992507574","https://openalex.org/W1999228575","https://openalex.org/W2000721204","https://openalex.org/W2039479881","https://openalex.org/W2103519107","https://openalex.org/W2109449402","https://openalex.org/W2113891116","https://openalex.org/W2115979064","https://openalex.org/W2116782674","https://openalex.org/W2135046866","https://openalex.org/W2135647798","https://openalex.org/W2137628444","https://openalex.org/W2139419267","https://openalex.org/W2140599235","https://openalex.org/W2142072340","https://openalex.org/W2142405592","https://openalex.org/W2142635246","https://openalex.org/W2145417574","https://openalex.org/W2146571341","https://openalex.org/W2148154358","https://openalex.org/W2150940164","https://openalex.org/W2154191559","https://openalex.org/W2154332973","https://openalex.org/W2161623414","https://openalex.org/W2162654459","https://openalex.org/W2997644599","https://openalex.org/W3133765915","https://openalex.org/W3140968660","https://openalex.org/W3149745985","https://openalex.org/W4285719527","https://openalex.org/W6636690510","https://openalex.org/W6682241100"],"related_works":["https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W3142333283","https://openalex.org/W2580650124","https://openalex.org/W3122088529","https://openalex.org/W3041320102","https://openalex.org/W2111669074","https://openalex.org/W2085259108","https://openalex.org/W3123087812","https://openalex.org/W2071416974"],"abstract_inverted_index":{"In":[0],"this":[1,48],"paper,":[2],"we":[3],"develop":[4],"a":[5,201,219,260],"sparse":[6,64,142,231],"variational":[7,80],"Bayesian":[8],"(VB)":[9],"extension":[10],"of":[11,23,26,33,43,84,93,101,104,111,130,155,165,222,229],"the":[12,19,24,31,44,68,79,85,99,102,109,112,128,131,136,141,147,156,166,170,187,223,230],"space-alternating":[13],"generalized":[14],"expectation-maximization":[15],"(SAGE)":[16],"algorithm":[17,45,66,71,158,233,251],"for":[18,57,127,160,169,207,218],"high":[20],"resolution":[21],"estimation":[22,52,100,110,240],"parameters":[25,88,114],"relevant":[27,105,224],"multipath":[28,86,106,132,189,225],"components":[29,107],"in":[30,47,72,244,259],"response":[32],"frequency":[34],"and":[35,97,108,145,214,234],"spatially":[36],"selective":[37],"wireless":[38],"channels.":[39,249],"The":[40,62,118,153,195,227,250],"application":[41],"context":[42],"considered":[46,191],"contribution":[49],"is":[50,120,252],"parameter":[51,94],"from":[53],"channel":[54,59,239],"sounding":[55],"measurements":[56],"radio":[58],"modeling":[60],"purpose.":[61],"new":[63],"VB-SAGE":[65,143,157,232],"extends":[67],"classical":[69],"SAGE":[70],"two":[73],"respects:":[74],"i)":[75],"by":[76,122,149],"monotonically":[77],"minimizing":[78],"free":[81],"energy,":[82],"distributions":[83],"component":[87,113,190],"can":[89],"be":[90],"obtained":[91],"instead":[92],"point":[95],"estimates":[96],"ii)":[98],"number":[103],"are":[115,198,242],"implemented":[116],"jointly.":[117],"sparsity":[119,125,138,171],"achieved":[121],"defining":[123],"parametric":[124],"priors":[126,139],"weights":[129],"components.":[133,226],"We":[134],"revisit":[135],"Gaussian":[137],"within":[140],"framework":[144],"extend":[146],"results":[148],"considering":[150],"Laplace":[151],"priors.":[152],"structure":[154],"allows":[159],"an":[161],"analytical":[162],"stability":[163],"analysis":[164,174],"update":[167],"expression":[168],"parameters.":[172],"This":[173],"leads":[175],"to":[176,186,204,255],"fast,":[177],"computationally":[178],"simple,":[179],"yet":[180],"powerful,":[181],"adaptive":[182],"selection":[183,196],"criteria":[184,197],"applied":[185,254],"single":[188],"at":[192],"each":[193],"iteration.":[194],"adjusted":[199],"on":[200],"per-component-SNR":[202],"basis":[203],"better":[205],"account":[206],"model":[208],"mismatches,":[209],"e.g.,":[210],"diffuse":[211],"scattering,":[212],"calibration":[213],"discretization":[215],"errors,":[216],"allowing":[217],"robust":[220],"extraction":[221],"performance":[228],"its":[235],"advantages":[236],"over":[237],"conventional":[238],"methods":[241],"demonstrated":[243],"synthetic":[245],"single-input-multiple-output":[246],"(SIMO)":[247],"time-invariant":[248,263],"also":[253],"real":[256],"measurement":[257],"data":[258],"multiple-input-multiple-output":[261],"(MIMO)":[262],"context.":[264]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":9},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}