{"id":"https://openalex.org/W2207079798","doi":"https://doi.org/10.1109/eusipco.2015.7362553","title":"Separation matrix optimization using associative memory model for blind source separation","display_name":"Separation matrix optimization using associative memory model for blind source separation","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W2207079798","doi":"https://doi.org/10.1109/eusipco.2015.7362553","mag":"2207079798"},"language":"en","primary_location":{"id":"doi:10.1109/eusipco.2015.7362553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eusipco.2015.7362553","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":"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/A5088171135","display_name":"Motoi Omachi","orcid":"https://orcid.org/0000-0002-9159-4371"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Motoi Omachi","raw_affiliation_strings":["Department of the computer science, Waseda University, Japan"],"affiliations":[{"raw_affiliation_string":"Department of the computer science, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087632404","display_name":"Tetsuji Ogawa","orcid":"https://orcid.org/0000-0002-7316-2073"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuji Ogawa","raw_affiliation_strings":["Department of the computer science, Waseda University, Japan"],"affiliations":[{"raw_affiliation_string":"Department of the computer science, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101188700","display_name":"Tetsunori Kobayashi","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsunori Kobayashi","raw_affiliation_strings":["Department of the computer science, Waseda University, Japan"],"affiliations":[{"raw_affiliation_string":"Department of the computer science, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080960862","display_name":"Masaru Fujieda","orcid":null},"institutions":[{"id":"https://openalex.org/I28777237","display_name":"Oki Electric Industry (Japan)","ror":"https://ror.org/0503rt987","country_code":"JP","type":"company","lineage":["https://openalex.org/I28777237"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaru Fujieda","raw_affiliation_strings":["Oki Electric Industry Co., Ltd., Japan"],"affiliations":[{"raw_affiliation_string":"Oki Electric Industry Co., Ltd., Japan","institution_ids":["https://openalex.org/I28777237"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110478009","display_name":"Kazuhiro Katagiri","orcid":null},"institutions":[{"id":"https://openalex.org/I28777237","display_name":"Oki Electric Industry (Japan)","ror":"https://ror.org/0503rt987","country_code":"JP","type":"company","lineage":["https://openalex.org/I28777237"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuhiro Katagiri","raw_affiliation_strings":["Oki Electric Industry Co., Ltd., Japan"],"affiliations":[{"raw_affiliation_string":"Oki Electric Industry Co., Ltd., Japan","institution_ids":["https://openalex.org/I28777237"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5088171135"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":0.2872,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57060401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1098","last_page":"1102"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","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/T11447","display_name":"Blind Source Separation Techniques","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/T10860","display_name":"Speech and Audio Processing","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":0.9984999895095825,"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/blind-signal-separation","display_name":"Blind signal separation","score":0.7975654006004333},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.6239928603172302},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6051942110061646},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.5692973732948303},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5265855193138123},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5231376886367798},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5194070339202881},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49320024251937866},{"id":"https://openalex.org/keywords/generalized-normal-distribution","display_name":"Generalized normal distribution","score":0.472316712141037},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.46704357862472534},{"id":"https://openalex.org/keywords/separation","display_name":"Separation (statistics)","score":0.43650195002555847},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4240809679031372},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28982412815093994},{"id":"https://openalex.org/keywords/normal-distribution","display_name":"Normal distribution","score":0.15664660930633545},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11357718706130981},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10171645879745483}],"concepts":[{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.7975654006004333},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.6239928603172302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6051942110061646},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.5692973732948303},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5265855193138123},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5231376886367798},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5194070339202881},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49320024251937866},{"id":"https://openalex.org/C171383496","wikidata":"https://www.wikidata.org/wiki/Q2497477","display_name":"Generalized normal distribution","level":3,"score":0.472316712141037},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.46704357862472534},{"id":"https://openalex.org/C2776061190","wikidata":"https://www.wikidata.org/wiki/Q7451805","display_name":"Separation (statistics)","level":2,"score":0.43650195002555847},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4240809679031372},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28982412815093994},{"id":"https://openalex.org/C102094743","wikidata":"https://www.wikidata.org/wiki/Q133871","display_name":"Normal distribution","level":2,"score":0.15664660930633545},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11357718706130981},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10171645879745483},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"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/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/eusipco.2015.7362553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eusipco.2015.7362553","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":15,"referenced_works":["https://openalex.org/W1963950237","https://openalex.org/W2025768430","https://openalex.org/W2027884847","https://openalex.org/W2031583051","https://openalex.org/W2031647436","https://openalex.org/W2036242736","https://openalex.org/W2072548008","https://openalex.org/W2078528584","https://openalex.org/W2079226880","https://openalex.org/W2114187103","https://openalex.org/W2120838354","https://openalex.org/W2159466547","https://openalex.org/W2170768669","https://openalex.org/W2296581541","https://openalex.org/W6683339014"],"related_works":["https://openalex.org/W1509813908","https://openalex.org/W2031820693","https://openalex.org/W3024816962","https://openalex.org/W973023320","https://openalex.org/W1910172735","https://openalex.org/W2118307209","https://openalex.org/W2107364365","https://openalex.org/W2539388437","https://openalex.org/W2107688514","https://openalex.org/W2137288760"],"abstract_inverted_index":{"A":[0],"source":[1,20,47],"signal":[2,52,112],"is":[3],"estimated":[4,111],"using":[5,97],"an":[6,98,107],"associative":[7],"memory":[8],"model":[9],"(AMM)":[10],"and":[11,27,65,100,113],"used":[12],"for":[13,74],"separation":[14,21,48,78,103,123],"matrix":[15,79,104],"optimization":[16],"in":[17,45,120],"linear":[18,77],"blind":[19],"(BSS)":[22],"to":[23,42,105],"yield":[24],"high":[25],"quality":[26],"less":[28],"distorted":[29],"speech.":[30],"Linear-filtering-based":[31],"BSS,":[32],"such":[33],"as":[34],"independent":[35,64],"vector":[36],"analysis":[37],"(IVA),":[38],"has":[39],"been":[40],"shown":[41],"be":[43],"effective":[44],"sound":[46,61],"while":[49],"avoiding":[50],"non-linear":[51],"distortion.":[53],"This":[54],"technique,":[55],"however,":[56],"requires":[57],"several":[58],"assumptions":[59,82],"of":[60],"sources":[62,85],"being":[63],"generated":[66],"from":[67],"non-Gaussian":[68],"distribution.":[69],"We":[70],"propose":[71],"a":[72,76],"method":[73,128],"estimating":[75,92],"without":[80],"any":[81],"about":[83],"the":[84,88,102,110,126,131],"by":[86,96,135],"repeating":[87],"following":[89],"two":[90],"steps:":[91],"non-distorted":[93],"reference":[94,114],"signals":[95],"AMM":[99],"optimizing":[101],"minimize":[106],"error":[108],"between":[109],"signal.":[115],"Experimental":[116],"comparisons":[117],"carried":[118],"out":[119],"simultaneous":[121],"speech":[122],"suggest":[124],"that":[125],"proposed":[127],"can":[129],"reduce":[130],"residual":[132],"distortion":[133],"caused":[134],"IVA.":[136]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}