{"id":"https://openalex.org/W2052897490","doi":"https://doi.org/10.1109/sam.2014.6882342","title":"Estimation of inter-channel phase differences using non-negative matrix factorization","display_name":"Estimation of inter-channel phase differences using non-negative matrix factorization","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2052897490","doi":"https://doi.org/10.1109/sam.2014.6882342","mag":"2052897490"},"language":"en","primary_location":{"id":"doi:10.1109/sam.2014.6882342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sam.2014.6882342","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","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/A5050320681","display_name":"Hendrik Kayser","orcid":"https://orcid.org/0000-0001-8200-992X"},"institutions":[{"id":"https://openalex.org/I4210144375","display_name":"Hearing4all","ror":"https://ror.org/0393vzh87","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210144375"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Hendrik Kayser","raw_affiliation_strings":["Medizinische Physik and Cluster of Excellence Hearing4all, Universit\u00e4t Oldenburg, Oldenburg, Germany","Med. Phys. & Cluster of Excellence Hearing4all, Univ. Oldenburg, Oldenburg, Germany"],"affiliations":[{"raw_affiliation_string":"Medizinische Physik and Cluster of Excellence Hearing4all, Universit\u00e4t Oldenburg, Oldenburg, Germany","institution_ids":["https://openalex.org/I4210144375"]},{"raw_affiliation_string":"Med. Phys. & Cluster of Excellence Hearing4all, Univ. Oldenburg, Oldenburg, Germany","institution_ids":["https://openalex.org/I4210144375"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009092572","display_name":"J\u00f6rn Anem\u00fcller","orcid":"https://orcid.org/0000-0001-5564-5795"},"institutions":[{"id":"https://openalex.org/I4210144375","display_name":"Hearing4all","ror":"https://ror.org/0393vzh87","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210144375"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jorn Anemuller","raw_affiliation_strings":["Medizinische Physik and Cluster of Excellence Hearing4all, Universit\u00e4t Oldenburg, Oldenburg, Germany","Med. Phys. & Cluster of Excellence Hearing4all, Univ. Oldenburg, Oldenburg, Germany"],"affiliations":[{"raw_affiliation_string":"Medizinische Physik and Cluster of Excellence Hearing4all, Universit\u00e4t Oldenburg, Oldenburg, Germany","institution_ids":["https://openalex.org/I4210144375"]},{"raw_affiliation_string":"Med. Phys. & Cluster of Excellence Hearing4all, Univ. Oldenburg, Oldenburg, Germany","institution_ids":["https://openalex.org/I4210144375"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010480213","display_name":"Kamil Adilo\u011flu","orcid":"https://orcid.org/0000-0003-0172-8485"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kamil Adiloglu","raw_affiliation_strings":["H\u00f6rTech gGmbH Center of Competence, Research and Development, Marie-Curie-Str. 2, 26129 Oldenburg, Germany","Res. & Dev, HorTech gGmbH Center of Competence, Oldenburg, Germany"],"affiliations":[{"raw_affiliation_string":"H\u00f6rTech gGmbH Center of Competence, Research and Development, Marie-Curie-Str. 2, 26129 Oldenburg, Germany","institution_ids":[]},{"raw_affiliation_string":"Res. & Dev, HorTech gGmbH Center of Competence, Oldenburg, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5050320681"],"corresponding_institution_ids":["https://openalex.org/I4210144375"],"apc_list":null,"apc_paid":null,"fwci":1.1646,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78942191,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"92","issue":null,"first_page":"77","last_page":"80"},"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":0.9991999864578247,"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":0.9990000128746033,"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/matrix-decomposition","display_name":"Matrix decomposition","score":0.766666054725647},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7035757303237915},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6875402331352234},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.6517261862754822},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5512229204177856},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5467480421066284},{"id":"https://openalex.org/keywords/phase","display_name":"Phase (matter)","score":0.5351223945617676},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.4975581467151642},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4862595796585083},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.47023293375968933},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.44902077317237854},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.419152170419693},{"id":"https://openalex.org/keywords/audio-signal","display_name":"Audio signal","score":0.4174154996871948},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.41264063119888306},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.17988580465316772},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.15086495876312256},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1333179771900177}],"concepts":[{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.766666054725647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7035757303237915},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6875402331352234},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.6517261862754822},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5512229204177856},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5467480421066284},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.5351223945617676},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4975581467151642},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4862595796585083},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.47023293375968933},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.44902077317237854},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.419152170419693},{"id":"https://openalex.org/C64922751","wikidata":"https://www.wikidata.org/wiki/Q4650799","display_name":"Audio signal","level":3,"score":0.4174154996871948},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.41264063119888306},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.17988580465316772},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.15086495876312256},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1333179771900177},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sam.2014.6882342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sam.2014.6882342","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2013608223","https://openalex.org/W2013969331","https://openalex.org/W2039844283","https://openalex.org/W2046317813","https://openalex.org/W2100818340","https://openalex.org/W2113990625","https://openalex.org/W2127851351","https://openalex.org/W2964080492","https://openalex.org/W6629162733"],"related_works":["https://openalex.org/W2037504162","https://openalex.org/W2774154397","https://openalex.org/W2146544734","https://openalex.org/W2921513691","https://openalex.org/W2156699640","https://openalex.org/W2098101267","https://openalex.org/W1979654135","https://openalex.org/W2156181515","https://openalex.org/W1984255382","https://openalex.org/W2576645943"],"abstract_inverted_index":{"Estimation":[0],"of":[1,11,34,69,79,135],"non-linearities":[2,36],"in":[3,22,37,42,133],"phase":[4,62,96,129],"differences":[5,63,97,130],"between":[6,54],"two":[7],"or":[8],"more":[9,18],"channels":[10,56],"an":[12],"audio":[13,23,40,115],"recording":[14],"leads":[15],"to":[16],"a":[17,67,84,123],"precise":[19],"spatial":[20],"information":[21],"signal":[24],"enhancement":[25],"applications.":[26],"In":[27,114],"this":[28,46],"work,":[29],"we":[30,48],"propose":[31],"the":[32,55,59,80,93,99,102,106,110,119],"estimation":[33],"these":[35],"multi-channel,":[38],"multi-source":[39],"mixtures":[41],"reverberant":[43],"environments.":[44],"For":[45],"task,":[47],"compute":[49],"short":[50],"term":[51],"cross-correlation":[52,81],"functions":[53],"and":[57],"extract":[58],"non-linear":[60],"inter-channel":[61,95],"as":[64,66],"well":[65],"measure":[68],"activation":[70],"for":[71],"each":[72],"source.":[73],"This":[74],"is":[75],"conducted":[76],"by":[77,131],"decomposition":[78],"matrix":[82,86],"using":[83],"non-negative":[85],"factorization":[87],"method.":[88],"Our":[89],"evaluation":[90],"shows":[91],"that":[92],"estimated":[94,103],"depict":[98],"non-linearities.":[100],"Furthermore,":[101],"activations":[104],"reflect":[105],"time":[107],"instances":[108],"where":[109],"sources":[111],"are":[112],"active.":[113],"source":[116],"separation":[117],"experiments":[118],"proposed":[120],"method":[121],"outperforms":[122],"state-of-the-art":[124],"approach":[125],"based":[126],"on":[127],"linear":[128],"30%":[132],"terms":[134],"relative":[136],"improvement.":[137]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
