{"id":"https://openalex.org/W2407780738","doi":"https://doi.org/10.21437/interspeech.2014-508","title":"Weighted spatial bispectrum correlation matrix for DOA estimation in the presence of interferences","display_name":"Weighted spatial bispectrum correlation matrix for DOA estimation in the presence of interferences","publication_year":2014,"publication_date":"2014-09-14","ids":{"openalex":"https://openalex.org/W2407780738","doi":"https://doi.org/10.21437/interspeech.2014-508","mag":"2407780738"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2014-508","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2014-508","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2014","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/A5100652844","display_name":"Wei Xue","orcid":"https://orcid.org/0000-0002-4942-7748"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wei Xue","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108575841","display_name":"Shan Liang","orcid":"https://orcid.org/0000-0002-9734-9166"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shan Liang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5039635290","display_name":"Wenju Liu","orcid":"https://orcid.org/0000-0001-9088-8282"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenju Liu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100652844"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5823,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.7115329,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2228","last_page":"2232"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":1.0,"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":1.0,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"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":0.9994999766349792,"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/bispectrum","display_name":"Bispectrum","score":0.9599906206130981},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7210065722465515},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6704211831092834},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6123796105384827},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.5617626309394836},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5189878344535828},{"id":"https://openalex.org/keywords/direction-of-arrival","display_name":"Direction of arrival","score":0.4895645081996918},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46891555190086365},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4393315315246582},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3797871470451355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3217772841453552},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3099004626274109},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22557684779167175},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.16007795929908752},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.07690590620040894},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07464134693145752},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07341563701629639},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07260781526565552}],"concepts":[{"id":"https://openalex.org/C114148568","wikidata":"https://www.wikidata.org/wiki/Q2410583","display_name":"Bispectrum","level":3,"score":0.9599906206130981},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7210065722465515},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6704211831092834},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6123796105384827},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.5617626309394836},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5189878344535828},{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.4895645081996918},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46891555190086365},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4393315315246582},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3797871470451355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3217772841453552},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3099004626274109},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22557684779167175},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.16007795929908752},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.07690590620040894},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07464134693145752},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07341563701629639},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07260781526565552},{"id":"https://openalex.org/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","level":2,"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":2,"locations":[{"id":"doi:10.21437/interspeech.2014-508","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2014-508","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2014","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-125515","is_oa":false,"landing_page_url":"https://repository.hkust.edu.hk/ir/Record/1783.1-125515","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1864613704","https://openalex.org/W1974387177","https://openalex.org/W2013913072","https://openalex.org/W2016637789","https://openalex.org/W2045352743","https://openalex.org/W2067584370","https://openalex.org/W2072313414","https://openalex.org/W2097525122","https://openalex.org/W2101422368","https://openalex.org/W2113638573","https://openalex.org/W2114219351","https://openalex.org/W2121973264","https://openalex.org/W2128977628","https://openalex.org/W2170066937","https://openalex.org/W2403482919"],"related_works":["https://openalex.org/W2541615194","https://openalex.org/W2357592863","https://openalex.org/W2002943794","https://openalex.org/W2351984395","https://openalex.org/W2544518984","https://openalex.org/W2371303008","https://openalex.org/W2093925636","https://openalex.org/W4382204317","https://openalex.org/W2100915163","https://openalex.org/W2113817303"],"abstract_inverted_index":{"Besides":[0],"the":[1,5,13,18,38,58,68,87,91,97,102,108,112,119,124,131,137,148],"undirected":[2,29],"environmental":[3],"noise,":[4],"surrounding":[6],"interference":[7,49],"also":[8],"brings":[9],"great":[10],"challenges":[11],"to":[12,117,129,135],"robust":[14,50],"DOA":[15,23,51,80],"estimation":[16,24,52],"of":[17,72,90,147,159],"speech":[19,121],"source.":[20],"As":[21],"conventional":[22],"methods":[25],"always":[26],"assume":[27],"an":[28],"noise":[30],"model,":[31],"they":[32],"usually":[33],"cannot":[34],"perform":[35],"reliably":[36],"when":[37],"strong":[39],"inference":[40],"exists.":[41],"In":[42,110,133],"this":[43],"paper,":[44],"we":[45],"propose":[46],"a":[47,78,140],"novel":[48],"method,":[53],"which":[54,126],"is":[55,82,143,151],"based":[56,85],"on":[57,86],"\"weighted":[59],"spatial":[60,69],"bispectrum":[61,73,115,138],"correlation":[62,70],"matrix":[63],"(WSBCM)\".":[64],"The":[65,145],"WSBCM":[66,113],"contains":[67],"information":[71,105],"phase":[74],"difference":[75],"(BPD),":[76],"and":[77],"new":[79],"estimator":[81],"further":[83,127],"derived":[84],"eigenvalue":[88],"analysis":[89],"WSBCM.":[92],"By":[93],"formulating":[94],"with":[95],"WSBCM,":[96],"proposed":[98,149],"method":[99,150],"benefits":[100],"from":[101],"redundant":[103],"DOA-related":[104],"provided":[106],"by":[107,153],"BPD.":[109],"addition,":[111],"enables":[114],"weighting":[116],"highlight":[118],"pure":[120],"units":[122],"in":[123],"bispectrum,":[125],"helps":[128],"improve":[130],"performance.":[132],"order":[134],"compute":[136],"weights,":[139],"decision-directed":[141],"approach":[142],"derived.":[144],"effectiveness":[146],"demonstrated":[152],"experiments":[154],"conducted":[155],"under":[156],"various":[157],"kinds":[158],"interference-existing":[160],"scenarios.":[161]},"counts_by_year":[{"year":2015,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
