{"id":"https://openalex.org/W2048935155","doi":"https://doi.org/10.1109/icassp.2014.6853858","title":"Examples of optimal noise reduction filters derived from the squared Pearson correlation coefficient","display_name":"Examples of optimal noise reduction filters derived from the squared Pearson correlation coefficient","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2048935155","doi":"https://doi.org/10.1109/icassp.2014.6853858","mag":"2048935155"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2014.6853858","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6853858","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 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/A5077321767","display_name":"Jiaolong Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaolong Yu","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, Shaanxi, China","Northwestern Polytech. Univ., Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"Northwestern Polytech. Univ., Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071376063","display_name":"Jacob Benesty","orcid":"https://orcid.org/0000-0002-0036-5865"},"institutions":[{"id":"https://openalex.org/I159129438","display_name":"Universit\u00e9 du Qu\u00e9bec \u00e0 Montr\u00e9al","ror":"https://ror.org/002rjbv21","country_code":"CA","type":"education","lineage":["https://openalex.org/I159129438","https://openalex.org/I49663120"]},{"id":"https://openalex.org/I39481719","display_name":"Institut National de la Recherche Scientifique","ror":"https://ror.org/04td37d32","country_code":"CA","type":"education","lineage":["https://openalex.org/I39481719","https://openalex.org/I49663120"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jacob Benesty","raw_affiliation_strings":["EMT, University of Quebec, Montreal, QC, Canada","[INRS-EMT, University of Quebec, Montr\u00e9al, QC, Canada]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EMT, University of Quebec, Montreal, QC, Canada","institution_ids":["https://openalex.org/I159129438"]},{"raw_affiliation_string":"[INRS-EMT, University of Quebec, Montr\u00e9al, QC, Canada]","institution_ids":["https://openalex.org/I159129438","https://openalex.org/I39481719"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034257180","display_name":"Gongping Huang","orcid":"https://orcid.org/0000-0002-6825-7473"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gongping Huang","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, Shaanxi, China","Northwestern Polytech. Univ., Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"Northwestern Polytech. Univ., Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056129529","display_name":"Jingdong Chen","orcid":"https://orcid.org/0000-0003-0083-9247"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingdong Chen","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, Shaanxi, China","Northwestern Polytech. Univ., Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"Northwestern Polytech. Univ., Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2423,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.78884573,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"assp 27","issue":null,"first_page":"1552","last_page":"1556"},"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/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"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9940999746322632,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6450306177139282},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6389934420585632},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6232967376708984},{"id":"https://openalex.org/keywords/wiener-filter","display_name":"Wiener filter","score":0.5947695970535278},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5723364949226379},{"id":"https://openalex.org/keywords/minimum-mean-square-error","display_name":"Minimum mean square error","score":0.5575582981109619},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.5574550032615662},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.4770902097225189},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.455921471118927},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3712550699710846},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2977638244628906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.13005316257476807}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6450306177139282},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6389934420585632},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6232967376708984},{"id":"https://openalex.org/C18537770","wikidata":"https://www.wikidata.org/wiki/Q25523","display_name":"Wiener filter","level":2,"score":0.5947695970535278},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5723364949226379},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.5575582981109619},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.5574550032615662},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.4770902097225189},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.455921471118927},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3712550699710846},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2977638244628906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.13005316257476807},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2014.6853858","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6853858","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.887.9817","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.887.9817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://mirlab.org/conference_papers/International_Conference/ICASSP%202014/papers/p1571-yu.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W317957491","https://openalex.org/W342845560","https://openalex.org/W1495679096","https://openalex.org/W1968939597","https://openalex.org/W1975301756","https://openalex.org/W2000520546","https://openalex.org/W2000916836","https://openalex.org/W2096779346","https://openalex.org/W2102661631","https://openalex.org/W2112469598","https://openalex.org/W2116668371","https://openalex.org/W2121973264","https://openalex.org/W2128653836","https://openalex.org/W2163835077","https://openalex.org/W2164656607","https://openalex.org/W2168280933","https://openalex.org/W2914048585","https://openalex.org/W3031363333","https://openalex.org/W3108418035","https://openalex.org/W3147539069","https://openalex.org/W4245919820","https://openalex.org/W6611575399"],"related_works":["https://openalex.org/W2363395155","https://openalex.org/W2353350167","https://openalex.org/W2075897667","https://openalex.org/W4382982879","https://openalex.org/W2907746047","https://openalex.org/W2254945790","https://openalex.org/W2966246521","https://openalex.org/W3125536267","https://openalex.org/W4311044000","https://openalex.org/W2274645452"],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"the":[3,10,21,37,40,44,70,77,84,94,98],"problem":[4],"of":[5,39,96],"single-channel":[6],"noise":[7,28,52,58,100],"reduction":[8,29,101],"in":[9],"time":[11],"domain.":[12],"Based":[13],"on":[14],"some":[15],"orthogonal":[16],"decomposition":[17],"developed":[18],"recently":[19],"and":[20,57,60,72],"squared":[22],"Pearson":[23],"correlation":[24],"coefficient":[25],"(SPCC),":[26],"several":[27],"filters":[30,74],"are":[31,90],"derived.":[32],"We":[33,67],"will":[34],"show":[35],"that":[36],"optimization":[38],"SPCC":[41,78],"leads":[42],"to":[43,79,92],"Wiener,":[45],"minimum":[46,51,54,63],"variance":[47,64],"distortionless":[48],"response":[49],"(MVDR),":[50],"(MN),":[53],"uncorrelated":[55],"speech":[56],"(MUSN),":[59],"linearly":[61],"constrained":[62],"(LCMV)":[65],"filters.":[66,102],"also":[68],"compare":[69],"Wiener":[71],"MVDR":[73],"derived":[75,82],"from":[76,83],"their":[80],"counterparts":[81],"mean-square":[85],"error":[86],"(MSE)":[87],"criterion.":[88],"Simulations":[89],"provided":[91],"illustrate":[93],"performance":[95],"all":[97],"deduced":[99]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
