{"id":"https://openalex.org/W75015351","doi":null,"title":"UNDERDETERMINED BLIND SOURCE SEPARATION USING A PROBABILISTIC SOURCE SPARSITY MODEL","display_name":"UNDERDETERMINED BLIND SOURCE SEPARATION USING A PROBABILISTIC SOURCE SPARSITY MODEL","publication_year":2001,"publication_date":"2001-01-01","ids":{"openalex":"https://openalex.org/W75015351","mag":"75015351"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.11.6396","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.6396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ica2001.ucsd.edu/index_files/pdfs/036-vielva.pdf","raw_type":"text"},"volume":null,"type":"article","indexed_in":[],"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/A5078477873","display_name":"Luis Vielva","orcid":"https://orcid.org/0000-0001-9562-5334","observed_orcids":["https://orcid.org/0000-0001-9562-5334"]},"institutions":[{"id":"https://openalex.org/I13134134","display_name":"Universidad de Cantabria","ror":"https://ror.org/046ffzj20","country_code":"ES","type":"education","lineage":["https://openalex.org/I13134134"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Luis Vielva","raw_affiliation_strings":["University Of Cantabria"],"raw_orcid":"https://orcid.org/0000-0001-9562-5334","affiliations":[{"raw_affiliation_string":"University Of Cantabria","institution_ids":["https://openalex.org/I13134134"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083261801","display_name":"Deniz Erdogmus B","orcid":"https://orcid.org/0000-0002-1114-3539","observed_orcids":["https://orcid.org/0000-0002-1114-3539"]},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deniz Erdo\u011fmu\u015f","raw_affiliation_strings":["[University of Florida]"],"raw_orcid":"https://orcid.org/0000-0002-1114-3539","affiliations":[{"raw_affiliation_string":"[University of Florida]","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019504861","display_name":"Jos\u00e9 Carlos Pr\u00edncipe","orcid":"https://orcid.org/0000-0002-3449-3531","observed_orcids":["https://orcid.org/0000-0002-3449-3531"]},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jos\u00e9 C. Pr\u0131\u0301ncipe","raw_affiliation_strings":["[University of Florida]"],"raw_orcid":"https://orcid.org/0000-0002-3449-3531","affiliations":[{"raw_affiliation_string":"[University of Florida]","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.8586,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.93902936,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9984999895095825,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9984999895095825,"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":0.0005000000237487257,"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/T10860","display_name":"Speech and Audio Processing","score":0.00019999999494757503,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/blind-source-separation","display_name":"blind source separation","score":0.9750000238418579},{"id":"https://openalex.org/keywords/underdetermined-systems","display_name":"underdetermined systems","score":0.8270000219345093},{"id":"https://openalex.org/keywords/mixing-matrix-estimation","display_name":"mixing matrix estimation","score":0.7879999876022339},{"id":"https://openalex.org/keywords/inverse-problems","display_name":"inverse problems","score":0.4399999976158142},{"id":"https://openalex.org/keywords/source-statistics","display_name":"source statistics","score":0.5550000071525574}],"concepts":[{"id":"https://openalex.org/C179690561","wikidata":"https://www.wikidata.org/wiki/Q4316110","display_name":"Underdetermined system","level":2,"score":0.9587699770927429},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.814059317111969},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5844990611076355},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5196170210838318},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4911439120769501},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.48525428771972656},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.4689120054244995},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.4590398967266083},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.4574964642524719},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43080809712409973},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.4160594344139099},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41529133915901184},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4096670150756836},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.373757541179657},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35077816247940063},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2667553722858429},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.1135057806968689},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.11.6396","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.6396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ica2001.ucsd.edu/index_files/pdfs/036-vielva.pdf","raw_type":"text"},{"id":"mag:75015351","doi":null,"is_oa":false,"landing_page_url":"http://inc2.ucsd.edu/ica2001/036-vielva.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W184277047","https://openalex.org/W1527042480","https://openalex.org/W1576347883","https://openalex.org/W1667165204","https://openalex.org/W1964724001","https://openalex.org/W2036488048","https://openalex.org/W2038237443","https://openalex.org/W2092579730","https://openalex.org/W2105464873","https://openalex.org/W2119647652","https://openalex.org/W2139896607","https://openalex.org/W2154124003","https://openalex.org/W2798909945"],"related_works":["https://openalex.org/W7095955554","https://openalex.org/W2538077050","https://openalex.org/W1995395452","https://openalex.org/W2038237443","https://openalex.org/W7097470952","https://openalex.org/W2164034042","https://openalex.org/W2539370967","https://openalex.org/W7096363451","https://openalex.org/W7019033788","https://openalex.org/W7025269727"],"abstract_inverted_index":{"Blind":[0],"source":[1,7],"separation":[2],"consists":[3],"of":[4,17,58,62,73,89,120,123,128,147],"recovering":[5],"#":[6,10],"signals":[8,35],"from":[9],"measurements":[11],"that":[12,103],"are":[13],"an":[14,37,70],"unknown":[15],"function":[16],"the":[18,22,34,42,48,53,66,77,87,105,121,124,129,134],"sources.":[19,54,125],"In":[20,96],"solving":[21],"underdetermined":[23],"(###)":[24],"linear":[25,49],"problem":[26,50,68],"three":[27],"stages":[28],"can":[29],"be":[30,84],"identified:":[31],"to":[32,40,46,51,83,133],"represent":[33],"in":[36,109],"appropriate":[38],"domain,":[39],"estimate":[41,52],"mixing":[43],"matrix,":[44],"and":[45,139],"invert":[47],"As":[55],"a":[56,101,110],"consequence":[57],"having":[59],"more":[60],"degrees":[61],"freedom":[63],"than":[64],"constraints,":[65],"inverse":[67,137],"has":[69],"infinite":[71],"number":[72],"solutions.":[74],"To":[75],"choose":[76,104],"\"best\"":[78,106],"solution,":[79],"additional":[80],"constraints":[81],"have":[82],"imposed":[85],"on":[86],"basis":[88,114],"some":[90,117],"performance":[91],"criterion":[92],"or":[93],"previous":[94,118],"knowledge.":[95],"this":[97],"communication":[98],"we":[99],"present":[100],"method":[102],"demixing":[107],"matrix":[108],"sample":[111,113],"by":[112,115,145],"using":[116],"knowledge":[119],"statistics":[122],"The":[126],"behaviour":[127],"estimator":[130],"is":[131],"compared":[132],"global":[135],"pseudo":[136],"approach":[138],"with":[140],"other":[141],"local":[142],"heuristic":[143],"methods":[144],"means":[146],"Montecarlo":[148],"simulations.":[149]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2016-06-24T00:00:00"}
