{"id":"https://openalex.org/W1507620393","doi":"https://doi.org/10.1109/icassp.2015.7178644","title":"Multichannel Wiener filtering via multichannel decorrelation","display_name":"Multichannel Wiener filtering via multichannel decorrelation","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1507620393","doi":"https://doi.org/10.1109/icassp.2015.7178644","mag":"1507620393"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2015.7178644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2015.7178644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5112289133","display_name":"Philipp Th\u00fcne","orcid":null},"institutions":[{"id":"https://openalex.org/I904495901","display_name":"Ruhr University Bochum","ror":"https://ror.org/04tsk2644","country_code":"DE","type":"education","lineage":["https://openalex.org/I904495901"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Philipp Thune","raw_affiliation_strings":["Institute of Communication Acoustics (IKA), Ruhr-Universit\u00e4t Bochum, Bochum, Germany","Institute of Communication Acoustics (IKA), Ruhr-Universit\u00e4t Bochum, D-44780, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Communication Acoustics (IKA), Ruhr-Universit\u00e4t Bochum, Bochum, Germany","institution_ids":["https://openalex.org/I904495901"]},{"raw_affiliation_string":"Institute of Communication Acoustics (IKA), Ruhr-Universit\u00e4t Bochum, D-44780, Germany","institution_ids":["https://openalex.org/I904495901"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077936911","display_name":"Gerald Enzner","orcid":"https://orcid.org/0000-0002-3096-1342"},"institutions":[{"id":"https://openalex.org/I904495901","display_name":"Ruhr University Bochum","ror":"https://ror.org/04tsk2644","country_code":"DE","type":"education","lineage":["https://openalex.org/I904495901"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gerald Enzner","raw_affiliation_strings":["Institute of Communication Acoustics (IKA), Ruhr-Universit\u00e4t Bochum, Bochum, Germany","Institute of Communication Acoustics (IKA), Ruhr-Universit\u00e4t Bochum, D-44780, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Communication Acoustics (IKA), Ruhr-Universit\u00e4t Bochum, Bochum, Germany","institution_ids":["https://openalex.org/I904495901"]},{"raw_affiliation_string":"Institute of Communication Acoustics (IKA), Ruhr-Universit\u00e4t Bochum, D-44780, Germany","institution_ids":["https://openalex.org/I904495901"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I904495901"],"apc_list":null,"apc_paid":null,"fwci":0.4856,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.52865161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3611","last_page":"3615"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","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/T11447","display_name":"Blind Source Separation Techniques","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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/decorrelation","display_name":"Decorrelation","score":0.9159352779388428},{"id":"https://openalex.org/keywords/wiener-filter","display_name":"Wiener filter","score":0.7442619204521179},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.599013090133667},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5582308173179626},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5207719206809998},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.5136927962303162},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.49171143770217896},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4767918586730957},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.4549436569213867},{"id":"https://openalex.org/keywords/minimum-mean-square-error","display_name":"Minimum mean square error","score":0.4549436569213867},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.446260929107666},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4377676248550415},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.4303179979324341},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35063719749450684},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26479479670524597},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.19530615210533142},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.14938119053840637},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13797685503959656},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1200772225856781},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07651042938232422}],"concepts":[{"id":"https://openalex.org/C177860922","wikidata":"https://www.wikidata.org/wiki/Q788608","display_name":"Decorrelation","level":2,"score":0.9159352779388428},{"id":"https://openalex.org/C18537770","wikidata":"https://www.wikidata.org/wiki/Q25523","display_name":"Wiener filter","level":2,"score":0.7442619204521179},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.599013090133667},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5582308173179626},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5207719206809998},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.5136927962303162},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.49171143770217896},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4767918586730957},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.4549436569213867},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.4549436569213867},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.446260929107666},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4377676248550415},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.4303179979324341},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35063719749450684},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26479479670524597},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.19530615210533142},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.14938119053840637},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13797685503959656},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1200772225856781},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07651042938232422},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"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/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2015.7178644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2015.7178644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W167456299","https://openalex.org/W1492221128","https://openalex.org/W1572964346","https://openalex.org/W1931312565","https://openalex.org/W2036763972","https://openalex.org/W2046791564","https://openalex.org/W2075098731","https://openalex.org/W2093974379","https://openalex.org/W2099655464","https://openalex.org/W2110097273","https://openalex.org/W2113131123","https://openalex.org/W2113812096","https://openalex.org/W2113969889","https://openalex.org/W2114415559","https://openalex.org/W2121202969","https://openalex.org/W2121767183","https://openalex.org/W2133515443","https://openalex.org/W2134642725","https://openalex.org/W2139916917","https://openalex.org/W2141783538","https://openalex.org/W2143156057","https://openalex.org/W2146324387","https://openalex.org/W2149693148","https://openalex.org/W2150678643","https://openalex.org/W2155606012","https://openalex.org/W2158336491","https://openalex.org/W2169755932","https://openalex.org/W2296319761","https://openalex.org/W2797638056","https://openalex.org/W3147705998","https://openalex.org/W4214498238","https://openalex.org/W4231083737","https://openalex.org/W4250589301","https://openalex.org/W4302078450"],"related_works":["https://openalex.org/W1604939135","https://openalex.org/W2127058578","https://openalex.org/W2098040275","https://openalex.org/W4225141160","https://openalex.org/W2145997546","https://openalex.org/W4385778388","https://openalex.org/W2562252440","https://openalex.org/W2391894337","https://openalex.org/W2098233558","https://openalex.org/W4312751558"],"abstract_inverted_index":{"Extracting":[0],"a":[1,39,46,51,97],"target":[2],"source":[3,68],"signal":[4,17],"from":[5],"multiple":[6],"noisy":[7],"observations":[8],"is":[9,32,58],"an":[10,106],"essential":[11],"task":[12,37],"in":[13,38],"many":[14],"applications":[15],"of":[16,65,80,108,116,126,134],"processing":[18],"such":[19],"as":[20],"digital":[21],"communications":[22],"or":[23],"speech":[24],"and":[25,69,83,100,130],"audio":[26],"processing.":[27],"The":[28],"multi-channel":[29],"Wiener":[30,89],"filter":[31,48],"able":[33],"to":[34,61,87,104,138],"solve":[35],"this":[36,73,93],"minimum-mean-square-error":[40],"(MMSE)":[41],"optimal":[42],"way":[43],"by":[44,50],"applying":[45],"spatial":[47],"succeeded":[49],"spectral":[52],"postfilter.":[53],"Its":[54],"direct":[55],"implementation,":[56],"however,":[57],"difficult":[59],"due":[60],"requiring":[62],"the":[63,66,77,88,109,114,117,124,127,132,135,139],"statistics":[64,115],"unobservable":[67],"noise":[70],"signals.":[71],"In":[72],"paper,":[74],"we":[75,95],"apply":[76],"signal-separation-based":[78],"technique":[79],"multichannel":[81],"decorrelation":[82],"reveal":[84],"its":[85],"relation":[86],"post-filtering":[90],"component.":[91],"On":[92],"basis,":[94],"present":[96],"numerically":[98],"robust":[99],"efficient":[101],"adaptive":[102,136],"algorithm":[103,137],"find":[105],"estimate":[107],"MMSE-optimal":[110,140],"postfilter":[111,141],"based":[112],"on":[113],"observable":[118],"signals":[119],"alone.":[120],"Experimental":[121],"evaluation":[122],"demonstrates":[123],"validity":[125],"proposed":[128],"approach":[129],"confirms":[131],"convergence":[133],"solution.":[142]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}