{"id":"https://openalex.org/W2132106262","doi":"https://doi.org/10.1109/icassp.2009.4960050","title":"Joint estimation of signal and noise correlation matrices and its application to inverse filtering","display_name":"Joint estimation of signal and noise correlation matrices and its application to inverse filtering","publication_year":2009,"publication_date":"2009-04-01","ids":{"openalex":"https://openalex.org/W2132106262","doi":"https://doi.org/10.1109/icassp.2009.4960050","mag":"2132106262"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2009.4960050","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4960050","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","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/A5105269463","display_name":"Akira Tanaka","orcid":"https://orcid.org/0000-0003-0055-8234"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Akira Tanaka","raw_affiliation_strings":["Division of Computer Science, Hokkaido University, Sapporo, Japan","Division of Computer Science, Hokkaido University, N14N9, Kita-ku, Sapporo, 060-0814 Japan"],"affiliations":[{"raw_affiliation_string":"Division of Computer Science, Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]},{"raw_affiliation_string":"Division of Computer Science, Hokkaido University, N14N9, Kita-ku, Sapporo, 060-0814 Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060354017","display_name":"Masaaki Miyakoshi","orcid":null},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaaki Miyakoshi","raw_affiliation_strings":["Division of Computer Science, Hokkaido University, Sapporo, Japan","Division of Computer Science, Hokkaido University, N14N9, Kita-ku, Sapporo, 060-0814 Japan"],"affiliations":[{"raw_affiliation_string":"Division of Computer Science, Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]},{"raw_affiliation_string":"Division of Computer Science, Hokkaido University, N14N9, Kita-ku, Sapporo, 060-0814 Japan","institution_ids":["https://openalex.org/I205349734"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5105269463"],"corresponding_institution_ids":["https://openalex.org/I205349734"],"apc_list":null,"apc_paid":null,"fwci":2.8,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.90453884,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"e87 a","issue":null,"first_page":"2181","last_page":"2184"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.996999979019165,"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/T10860","display_name":"Speech and Audio Processing","score":0.9968000054359436,"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/wiener-filter","display_name":"Wiener filter","score":0.7363037467002869},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6548225283622742},{"id":"https://openalex.org/keywords/value-noise","display_name":"Value noise","score":0.5421290397644043},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5333625674247742},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.5202154517173767},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5000920295715332},{"id":"https://openalex.org/keywords/gradient-noise","display_name":"Gradient noise","score":0.49653416872024536},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4923516511917114},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.46540743112564087},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.45794835686683655},{"id":"https://openalex.org/keywords/wiener-deconvolution","display_name":"Wiener deconvolution","score":0.45252010226249695},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45072200894355774},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.41494932770729065},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.34801626205444336},{"id":"https://openalex.org/keywords/noise-floor","display_name":"Noise floor","score":0.33200347423553467},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.204604834318161},{"id":"https://openalex.org/keywords/blind-deconvolution","display_name":"Blind deconvolution","score":0.0944770872592926},{"id":"https://openalex.org/keywords/deconvolution","display_name":"Deconvolution","score":0.08851984143257141},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.07143282890319824},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06749272346496582}],"concepts":[{"id":"https://openalex.org/C18537770","wikidata":"https://www.wikidata.org/wiki/Q25523","display_name":"Wiener filter","level":2,"score":0.7363037467002869},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6548225283622742},{"id":"https://openalex.org/C182163834","wikidata":"https://www.wikidata.org/wiki/Q2926529","display_name":"Value noise","level":5,"score":0.5421290397644043},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5333625674247742},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5202154517173767},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5000920295715332},{"id":"https://openalex.org/C200378446","wikidata":"https://www.wikidata.org/wiki/Q4147391","display_name":"Gradient noise","level":5,"score":0.49653416872024536},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4923516511917114},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.46540743112564087},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.45794835686683655},{"id":"https://openalex.org/C15652857","wikidata":"https://www.wikidata.org/wiki/Q599016","display_name":"Wiener deconvolution","level":4,"score":0.45252010226249695},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45072200894355774},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.41494932770729065},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.34801626205444336},{"id":"https://openalex.org/C187612029","wikidata":"https://www.wikidata.org/wiki/Q17083130","display_name":"Noise floor","level":4,"score":0.33200347423553467},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.204604834318161},{"id":"https://openalex.org/C30044814","wikidata":"https://www.wikidata.org/wiki/Q11334452","display_name":"Blind deconvolution","level":3,"score":0.0944770872592926},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.08851984143257141},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.07143282890319824},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06749272346496582},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","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},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2009.4960050","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4960050","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322832","display_name":"University of Tokyo","ror":"https://ror.org/057zh3y96"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1479979375","https://openalex.org/W1510615751","https://openalex.org/W2063828588","https://openalex.org/W2098682358","https://openalex.org/W2099655464","https://openalex.org/W2113446502","https://openalex.org/W2128026204","https://openalex.org/W2147243899","https://openalex.org/W2260859552","https://openalex.org/W2797638056","https://openalex.org/W4302078450","https://openalex.org/W6630634331","https://openalex.org/W6674962817"],"related_works":["https://openalex.org/W134039041","https://openalex.org/W3125397569","https://openalex.org/W2810312662","https://openalex.org/W2032021057","https://openalex.org/W2118044916","https://openalex.org/W2353464957","https://openalex.org/W2588855097","https://openalex.org/W4315777920","https://openalex.org/W2057119739","https://openalex.org/W4240313311"],"abstract_inverted_index":{"Noise":[0],"suppression":[1],"by":[2,23],"linear":[3],"filters":[4],"for":[5,15],"a":[6,13],"time":[7],"series":[8],"is":[9,54,70,80,95],"discussed.":[10],"We":[11],"propose":[12],"method":[14],"jointly":[16],"estimating":[17],"signal":[18,88],"and":[19,89],"noise":[20,29,34,90,118],"correlation":[21,35,91,119],"matrices":[22],"incorporating":[24],"steering":[25,40],"vectors":[26,41],"of":[27,32,42,56,87,98,101,111,116],"the":[28,33,43,61,65,73,85,99,102,108,117],"or":[30],"eigenvectors":[31],"matrix":[36],"as":[37,39],"well":[38],"target":[44],"signals.":[45],"Our":[46],"estimates":[47,86],"bring":[48],"us":[49],"two":[50],"significant":[51],"advantages.":[52],"One":[53],"reduction":[55],"computational":[57],"cost":[58],"in":[59],"obtaining":[60],"Wiener":[62,66],"filter":[63,78],"since":[64,104],"post":[67],"filter,":[68],"which":[69],"combined":[71],"to":[72],"minimum":[74],"variance":[75],"distortionless":[76],"response":[77],"(MVDRF),":[79],"no":[81],"longer":[82],"needed":[83],"with":[84,113],"matrices.":[92],"The":[93],"other":[94],"an":[96,114],"improvement":[97],"performance":[100],"MVDRF":[103],"we":[105],"can":[106],"construct":[107],"regularized":[109],"version":[110],"it":[112],"estimate":[115],"matrix.":[120]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}