{"id":"https://openalex.org/W2902304208","doi":"https://doi.org/10.23919/eusipco.2018.8553007","title":"Performance analysis of the covariance-whitening and the covariance-subtraction methods for estimating the relative transfer function","display_name":"Performance analysis of the covariance-whitening and the covariance-subtraction methods for estimating the relative transfer function","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2902304208","doi":"https://doi.org/10.23919/eusipco.2018.8553007","mag":"2902304208"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2018.8553007","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-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/A5077008345","display_name":"Shmulik Markovich\u2010Golan","orcid":null},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Shmulik Markovich-Golan","raw_affiliation_strings":["Multimedia Comm. and Sig. Proc., Univ. Erlangen-Nuremberg, Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Multimedia Comm. and Sig. Proc., Univ. Erlangen-Nuremberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001052072","display_name":"Sharon Gannot","orcid":"https://orcid.org/0000-0002-2885-170X"},"institutions":[{"id":"https://openalex.org/I13955877","display_name":"Bar-Ilan University","ror":"https://ror.org/03kgsv495","country_code":"IL","type":"education","lineage":["https://openalex.org/I13955877"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Sharon Gannot","raw_affiliation_strings":["The Faculty of Engineering, Bar-Ilan University, Ramat-Gan, Israel"],"affiliations":[{"raw_affiliation_string":"The Faculty of Engineering, Bar-Ilan University, Ramat-Gan, Israel","institution_ids":["https://openalex.org/I13955877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068787682","display_name":"Walter Kellermann","orcid":"https://orcid.org/0000-0002-6501-3174"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Walter Kellermann","raw_affiliation_strings":["Multimedia Comm. and Sig. Proc., Univ. Erlangen-Nuremberg, Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Multimedia Comm. and Sig. Proc., Univ. Erlangen-Nuremberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077008345"],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":null,"apc_paid":null,"fwci":2.9726,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.92521382,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"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/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"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/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9994000196456909,"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":0.9987999796867371,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.7551857233047485},{"id":"https://openalex.org/keywords/covariance-function","display_name":"Covariance function","score":0.6155959367752075},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5990962386131287},{"id":"https://openalex.org/keywords/transfer-function","display_name":"Transfer function","score":0.5822961926460266},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5693436861038208},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5675539374351501},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5160667300224304},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.5058857798576355},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.4215020537376404},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.41419151425361633},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4106253981590271},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.34205904603004456},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3389400839805603},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22172731161117554},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22038617730140686},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11851686239242554},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07953229546546936}],"concepts":[{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.7551857233047485},{"id":"https://openalex.org/C137250428","wikidata":"https://www.wikidata.org/wiki/Q5178897","display_name":"Covariance function","level":3,"score":0.6155959367752075},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5990962386131287},{"id":"https://openalex.org/C81299745","wikidata":"https://www.wikidata.org/wiki/Q334269","display_name":"Transfer function","level":2,"score":0.5822961926460266},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5693436861038208},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5675539374351501},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5160667300224304},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.5058857798576355},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.4215020537376404},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.41419151425361633},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4106253981590271},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34205904603004456},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3389400839805603},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22172731161117554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22038617730140686},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11851686239242554},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07953229546546936},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2018.8553007","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W83404773","https://openalex.org/W978114954","https://openalex.org/W1497106521","https://openalex.org/W1503775994","https://openalex.org/W1970829267","https://openalex.org/W1974005055","https://openalex.org/W2011053773","https://openalex.org/W2016637789","https://openalex.org/W2037095848","https://openalex.org/W2060108923","https://openalex.org/W2069526386","https://openalex.org/W2115969105","https://openalex.org/W2144244295","https://openalex.org/W2147665979","https://openalex.org/W2148024641","https://openalex.org/W2155638623","https://openalex.org/W2568308529","https://openalex.org/W2791568767"],"related_works":["https://openalex.org/W2386803684","https://openalex.org/W1971337326","https://openalex.org/W3178402891","https://openalex.org/W651058035","https://openalex.org/W143964308","https://openalex.org/W2073389045","https://openalex.org/W2046078371","https://openalex.org/W4315750325","https://openalex.org/W4297832768","https://openalex.org/W2477374484"],"abstract_inverted_index":{"Estimation":[0],"of":[1,8,20,69,81,86,89],"the":[2,18,31,35,50,67,70,79,99,121,125,143],"relative":[3],"transfer":[4],"functions":[5],"(RTFs)":[6],"vector":[7],"a":[9,14],"desired":[10,90],"speech":[11,91],"source":[12,92],"is":[13,102,141],"fundamental":[15],"problem":[16],"in":[17,45,78,115,128],"design":[19],"data-dependent":[21],"spatial":[22],"filters.":[23],"We":[24],"present":[25],"two":[26],"common":[27],"estimation":[28],"methods,":[29],"namely":[30],"covariance-whitening":[32],"(CW)":[33],"and":[34,72,75,85,93],"covariance-subtraction":[36],"(CS)":[37],"methods.":[38],"The":[39,104],"CW":[40,71,100,122],"method":[41,101,123,127],"has":[42,58],"been":[43,60],"shown":[44],"prior":[46],"work":[47],"to":[48,111],"outperform":[49],"CS":[51,73,126],"method.":[52],"However,":[53],"thus":[54],"far":[55],"its":[56],"performance":[57,68],"not":[59,142],"analyzed.":[61],"In":[62,119],"this":[63,140],"paper,":[64],"we":[65],"analyze":[66],"methods":[74],"show":[76],"that":[77],"cases":[80],"spatially":[82],"white":[83],"noise":[84],"uniform":[87],"powers":[88],"coherent":[94],"interference":[95],"over":[96],"all":[97,129],"microphones,":[98],"superior.":[103],"derivations":[105],"are":[106],"validated":[107],"by":[108],"comparing":[109],"them":[110],"their":[112],"empirical":[113],"counterparts":[114],"Monte":[116],"Carlo":[117],"experiments.":[118],"fact,":[120],"outperforms":[124],"tested":[130],"scenarios,":[131],"although":[132],"there":[133],"may":[134],"be":[135],"rare":[136],"scenarios":[137],"for":[138],"which":[139],"case.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}