{"id":"https://openalex.org/W2997453778","doi":"https://doi.org/10.1109/waspaa.2019.8937171","title":"Independent Low-Rank Matrix Analysis with Decorrelation Learning","display_name":"Independent Low-Rank Matrix Analysis with Decorrelation Learning","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2997453778","doi":"https://doi.org/10.1109/waspaa.2019.8937171","mag":"2997453778"},"language":"en","primary_location":{"id":"doi:10.1109/waspaa.2019.8937171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/waspaa.2019.8937171","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)","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/A5084590882","display_name":"Rintaro Ikeshita","orcid":"https://orcid.org/0000-0003-2608-1999"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Rintaro Ikeshita","raw_affiliation_strings":["NTT Corporation,NTT Communication Science Laboratories,Kyoto,Japan","NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation,NTT Communication Science Laboratories,Kyoto,Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101438174","display_name":"Nobutaka Ito","orcid":"https://orcid.org/0000-0001-9740-6848"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nobutaka Ito","raw_affiliation_strings":["NTT Corporation,NTT Communication Science Laboratories,Kyoto,Japan","NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation,NTT Communication Science Laboratories,Kyoto,Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021240106","display_name":"Tomohiro Nakatani","orcid":"https://orcid.org/0000-0002-7487-7150"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomohiro Nakatani","raw_affiliation_strings":["NTT Corporation,NTT Communication Science Laboratories,Kyoto,Japan","NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation,NTT Communication Science Laboratories,Kyoto,Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007032557","display_name":"Hiroshi Sawada","orcid":"https://orcid.org/0000-0002-4831-9286"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Sawada","raw_affiliation_strings":["NTT Corporation,NTT Communication Science Laboratories,Kyoto,Japan","NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation,NTT Communication Science Laboratories,Kyoto,Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2251713219"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"288","last_page":"292"},"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":0.989300012588501,"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":0.9847999811172485,"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/decorrelation","display_name":"Decorrelation","score":0.9090365171432495},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.7936857342720032},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.7634475827217102},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.6151795387268066},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6107271313667297},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5256993770599365},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5226359367370605},{"id":"https://openalex.org/keywords/coordinate-descent","display_name":"Coordinate descent","score":0.5207640528678894},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.464771568775177},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4577580392360687},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.45388728380203247},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41799771785736084},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.41074705123901367},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4027464985847473},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36222928762435913},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3194080591201782}],"concepts":[{"id":"https://openalex.org/C177860922","wikidata":"https://www.wikidata.org/wiki/Q788608","display_name":"Decorrelation","level":2,"score":0.9090365171432495},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.7936857342720032},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.7634475827217102},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.6151795387268066},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6107271313667297},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5256993770599365},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5226359367370605},{"id":"https://openalex.org/C157553263","wikidata":"https://www.wikidata.org/wiki/Q5168004","display_name":"Coordinate descent","level":2,"score":0.5207640528678894},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.464771568775177},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4577580392360687},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.45388728380203247},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41799771785736084},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.41074705123901367},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4027464985847473},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36222928762435913},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3194080591201782},{"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/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","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},{"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/waspaa.2019.8937171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/waspaa.2019.8937171","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)","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":40,"referenced_works":["https://openalex.org/W41179353","https://openalex.org/W1592671018","https://openalex.org/W1876052200","https://openalex.org/W1980253826","https://openalex.org/W1982290653","https://openalex.org/W1983812858","https://openalex.org/W1992080197","https://openalex.org/W2014768838","https://openalex.org/W2027884847","https://openalex.org/W2039844283","https://openalex.org/W2042567328","https://openalex.org/W2072548008","https://openalex.org/W2099741732","https://openalex.org/W2113990625","https://openalex.org/W2114461480","https://openalex.org/W2119647652","https://openalex.org/W2124195644","https://openalex.org/W2127851351","https://openalex.org/W2128447814","https://openalex.org/W2128967371","https://openalex.org/W2135029798","https://openalex.org/W2137969290","https://openalex.org/W2142638745","https://openalex.org/W2154167944","https://openalex.org/W2164502538","https://openalex.org/W2170768669","https://openalex.org/W2408629183","https://openalex.org/W2412956798","https://openalex.org/W2804271779","https://openalex.org/W2903055851","https://openalex.org/W2903219940","https://openalex.org/W2905402910","https://openalex.org/W2987027330","https://openalex.org/W3098052090","https://openalex.org/W3143596294","https://openalex.org/W6601726404","https://openalex.org/W6678799340","https://openalex.org/W6680012447","https://openalex.org/W6714614974","https://openalex.org/W6715525401"],"related_works":["https://openalex.org/W2152159337","https://openalex.org/W2986257562","https://openalex.org/W1569917166","https://openalex.org/W2205924474","https://openalex.org/W2149098303","https://openalex.org/W2351387116","https://openalex.org/W2041930136","https://openalex.org/W1820098823","https://openalex.org/W2729215116","https://openalex.org/W2147305467"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,28,59,89,109,114],"determined":[4],"convolutive":[5],"blind":[6],"source":[7,38],"separation":[8,111],"(BSS)":[9],"problem.":[10],"The":[11],"state-of-the-art":[12],"independent":[13,19],"low-rank":[14],"matrix":[15,25],"analysis":[16,21],"(ILRMA),":[17],"unifying":[18],"component":[20],"(ICA)":[22],"and":[23,33,55,85,94],"nonnegative":[24],"factorization,":[26],"has":[27],"disadvantage":[29],"of":[30,37,70,91,113],"ignoring":[31],"inter-frame":[32],"inter-frequency":[34],"spectral":[35,53],"correlation":[36],"signals.":[39],"We":[40],"here":[41],"propose":[42],"a":[43,49,83],"new":[44],"BSS":[45],"method":[46,116],"that":[47,71],"estimates":[48],"linear":[50],"transformation":[51],"for":[52,72,88],"decorrelation":[54],"performs":[56],"ILRMA":[57],"in":[58],"transformed":[60],"domain.":[61],"A":[62],"newly":[63],"introduced":[64],"optimization":[65],"problem":[66],"is":[67],"an":[68],"extension":[69],"ICA":[73],"based":[74,97],"on":[75,98],"maximum":[76],"likelihood.":[77],"For":[78],"this":[79],"problem,":[80],"we":[81],"provide":[82],"necessary":[84],"sufficient":[86],"condition":[87],"existence":[90],"optimal":[92],"solutions,":[93],"develop":[95],"algorithms":[96],"block":[99],"coordinate":[100],"descent":[101],"methods":[102],"with":[103],"closed-form":[104],"solutions.":[105],"Experimental":[106],"results":[107],"show":[108],"improved":[110],"performance":[112],"proposed":[115],"compared":[117],"to":[118],"ILRMA.":[119]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":8}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}