{"id":"https://openalex.org/W2201820391","doi":"https://doi.org/10.1109/eusipco.2015.7362687","title":"Maximum likelihood and robust G-music performance in K-distributed noise","display_name":"Maximum likelihood and robust G-music performance in K-distributed noise","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W2201820391","doi":"https://doi.org/10.1109/eusipco.2015.7362687","mag":"2201820391"},"language":"en","primary_location":{"id":"doi:10.1109/eusipco.2015.7362687","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eusipco.2015.7362687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 23rd European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5112005763","display_name":"Yuri I. Abramovich","orcid":null},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yuri I. Abramovich","raw_affiliation_strings":["University of South Australia - ITR, Mawson Lakes, SA, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Australia - ITR, Mawson Lakes, SA, Australia","institution_ids":["https://openalex.org/I170239107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024539438","display_name":"Ben A. Johnson","orcid":"https://orcid.org/0000-0002-6653-967X"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ben A. Johnson","raw_affiliation_strings":["University of South Australia - ITR, Mawson Lakes, SA, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Australia - ITR, Mawson Lakes, SA, Australia","institution_ids":["https://openalex.org/I170239107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040395588","display_name":"Olivier Besson","orcid":"https://orcid.org/0000-0001-6079-8446"},"institutions":[{"id":"https://openalex.org/I17866349","display_name":"Universit\u00e9 F\u00e9d\u00e9rale de Toulouse Midi-Pyr\u00e9n\u00e9es","ror":"https://ror.org/004raaa70","country_code":"FR","type":"education","lineage":["https://openalex.org/I17866349"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Olivier Besson","raw_affiliation_strings":["University of Toulouse-ISAE, Toulouse, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toulouse-ISAE, Toulouse, France","institution_ids":["https://openalex.org/I17866349"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.12739851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1766","last_page":"1770"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9986000061035156,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9977999925613403,"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/maximum-likelihood","display_name":"Maximum likelihood","score":0.709924578666687},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6318789720535278},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6284372806549072},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6228803396224976},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.603251576423645},{"id":"https://openalex.org/keywords/multiple-signal-classification","display_name":"Multiple signal classification","score":0.5980331897735596},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5581035614013672},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5319764018058777},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.41015952825546265},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4001293182373047},{"id":"https://openalex.org/keywords/antenna","display_name":"Antenna (radio)","score":0.36101579666137695},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2944451570510864},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2834235429763794},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2635002136230469},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14530298113822937},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07520177960395813}],"concepts":[{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.709924578666687},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6318789720535278},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6284372806549072},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6228803396224976},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.603251576423645},{"id":"https://openalex.org/C206118826","wikidata":"https://www.wikidata.org/wiki/Q3841682","display_name":"Multiple signal classification","level":3,"score":0.5980331897735596},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5581035614013672},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5319764018058777},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.41015952825546265},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4001293182373047},{"id":"https://openalex.org/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","level":2,"score":0.36101579666137695},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2944451570510864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2834235429763794},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2635002136230469},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14530298113822937},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07520177960395813},{"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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":1,"locations":[{"id":"doi:10.1109/eusipco.2015.7362687","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eusipco.2015.7362687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 23rd European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1992511687","https://openalex.org/W2049983173","https://openalex.org/W2052364013","https://openalex.org/W2080249735","https://openalex.org/W2095307473","https://openalex.org/W2102388381","https://openalex.org/W2105502962","https://openalex.org/W2110905912","https://openalex.org/W2130693290","https://openalex.org/W2287886820","https://openalex.org/W3105672394","https://openalex.org/W6696147628"],"related_works":["https://openalex.org/W1975321310","https://openalex.org/W1952261593","https://openalex.org/W2014494654","https://openalex.org/W1970319972","https://openalex.org/W1578916557","https://openalex.org/W2953254336","https://openalex.org/W2112030392","https://openalex.org/W2109610499","https://openalex.org/W2465316997","https://openalex.org/W2201820391"],"abstract_inverted_index":{"For":[0],"an":[1,74],"antenna":[2],"array":[3],"input":[4],"mixture":[5],"of":[6,65],"m":[7],"point":[8],"source":[9],"signals":[10],"in":[11],"K-distributed":[12],"noise,":[13],"we":[14],"compare":[15],"DOA":[16],"estimation":[17],"delivered":[18],"by":[19],"Maximum":[20],"Likelihood":[21,58],"and":[22,69],"the":[23,35,46,56,63,79],"recently":[24],"introduced":[25],"Robust":[26],"G-MUSIC":[27],"(RG-MUSIC)":[28],"technique.":[29],"We":[30],"demonstrate":[31],"that":[32],"similar":[33],"to":[34,42,54,61],"Gaussian":[36,81],"case,":[37],"MLE":[38],"is":[39],"still":[40],"superior":[41],"RG-MUSIC,":[43],"especially":[44],"within":[45],"so-called":[47],"threshold":[48],"region.":[49],"This":[50],"makes":[51],"it":[52],"possible":[53],"use":[55],"Expected":[57],"(EL)":[59],"methodology":[60],"detect":[62],"presence":[64],"RG-MUSIC":[66],"performance":[67],"breakdown":[68],"\"cure\"":[70],"those":[71],"cases":[72],"via":[73],"approach":[75],"previously":[76],"developed":[77],"for":[78],"complex":[80],"circumstance.":[82]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}