{"id":"https://openalex.org/W4312774494","doi":"https://doi.org/10.1109/tim.2022.3216380","title":"Recursive Estimation of Multichannel Autoregressive Processes in Correlated Noise With Joint Instrumental Variable and Bias Compensation","display_name":"Recursive Estimation of Multichannel Autoregressive Processes in Correlated Noise With Joint Instrumental Variable and Bias Compensation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312774494","doi":"https://doi.org/10.1109/tim.2022.3216380"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3216380","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3216380","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5101730519","display_name":"Jiewei Li","orcid":"https://orcid.org/0000-0002-3148-4103"},"institutions":[{"id":"https://openalex.org/I4210145292","display_name":"Shenzhen University Health Science Center","ror":"https://ror.org/04yjbr930","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210145292"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Jiewei Li","raw_affiliation_strings":["School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China","Department of Electrical and Electronic Engineering, University of Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0002-3148-4103","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I4210145292"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, University of Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057049452","display_name":"S. C. Chan","orcid":"https://orcid.org/0000-0001-7212-4182"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shing Chow Chan","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-7212-4182","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064697038","display_name":"Yizhou Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yi Zhou Jiang","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-7023-6540","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036292248","display_name":"Bo Chai","orcid":"https://orcid.org/0000-0002-4976-1877"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Bo Chai","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-4976-1877","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1161,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.38012932,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","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/T11447","display_name":"Blind Source Separation Techniques","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/T10581","display_name":"Neural dynamics and brain function","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6565744280815125},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5525097846984863},{"id":"https://openalex.org/keywords/instrumental-variable","display_name":"Instrumental variable","score":0.5232997536659241},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5154379606246948},{"id":"https://openalex.org/keywords/recursive-least-squares-filter","display_name":"Recursive least squares filter","score":0.5094133019447327},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.496886283159256},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.48240792751312256},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44222456216812134},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.4413127601146698},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.42684975266456604},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.374143123626709},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.26385682821273804},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2468610405921936},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.233803391456604}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6565744280815125},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5525097846984863},{"id":"https://openalex.org/C162144332","wikidata":"https://www.wikidata.org/wiki/Q1665305","display_name":"Instrumental variable","level":2,"score":0.5232997536659241},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5154379606246948},{"id":"https://openalex.org/C145249878","wikidata":"https://www.wikidata.org/wiki/Q2835868","display_name":"Recursive least squares filter","level":3,"score":0.5094133019447327},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.496886283159256},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.48240792751312256},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44222456216812134},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4413127601146698},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.42684975266456604},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.374143123626709},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.26385682821273804},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2468610405921936},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.233803391456604},{"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":1,"locations":[{"id":"doi:10.1109/tim.2022.3216380","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3216380","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3119572867","display_name":null,"funder_award_id":"(2022SHIBS0003","funder_id":"https://openalex.org/F4320330381","funder_display_name":"Shenzhen-Hong Kong Institute of Brain Science"},{"id":"https://openalex.org/G8145940770","display_name":"\u60c5\u7eea\u52a0\u5de5\u8111\u673a\u5236\u53ca\u60c5\u7eea\u89e3\u7801\u4e0e\u8c03\u63a7\u7684\u9885\u5185\u8111\u7535\u7814\u7a76","funder_award_id":"61971289","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320330381","display_name":"Shenzhen-Hong Kong Institute of Brain Science","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W210359992","https://openalex.org/W1586900266","https://openalex.org/W1957346888","https://openalex.org/W1964769652","https://openalex.org/W1966264494","https://openalex.org/W1966969760","https://openalex.org/W1981181101","https://openalex.org/W1990002104","https://openalex.org/W2000326072","https://openalex.org/W2007240904","https://openalex.org/W2009604254","https://openalex.org/W2009914532","https://openalex.org/W2014294275","https://openalex.org/W2022081185","https://openalex.org/W2027673565","https://openalex.org/W2031114923","https://openalex.org/W2040739698","https://openalex.org/W2042179126","https://openalex.org/W2047654663","https://openalex.org/W2048413940","https://openalex.org/W2068494397","https://openalex.org/W2069300914","https://openalex.org/W2074055492","https://openalex.org/W2074501647","https://openalex.org/W2080992214","https://openalex.org/W2089957712","https://openalex.org/W2091683338","https://openalex.org/W2102246454","https://openalex.org/W2105967858","https://openalex.org/W2106258988","https://openalex.org/W2107896723","https://openalex.org/W2111105339","https://openalex.org/W2113762408","https://openalex.org/W2116255192","https://openalex.org/W2122779869","https://openalex.org/W2128404709","https://openalex.org/W2136562407","https://openalex.org/W2139931613","https://openalex.org/W2149094129","https://openalex.org/W2158631449","https://openalex.org/W2158674205","https://openalex.org/W2162365181","https://openalex.org/W2171419871","https://openalex.org/W2171490954","https://openalex.org/W2346353886","https://openalex.org/W2404594948","https://openalex.org/W2405546682","https://openalex.org/W2504952917","https://openalex.org/W2567137845","https://openalex.org/W2568392743","https://openalex.org/W2745804694","https://openalex.org/W2903357735","https://openalex.org/W2943118511","https://openalex.org/W2973190484","https://openalex.org/W2980784807","https://openalex.org/W2996389006","https://openalex.org/W3008977765","https://openalex.org/W3026124740","https://openalex.org/W3127935830","https://openalex.org/W3152205189","https://openalex.org/W4251492604","https://openalex.org/W4302770171","https://openalex.org/W4309573086","https://openalex.org/W6675857602","https://openalex.org/W6677299479","https://openalex.org/W6713165434"],"related_works":["https://openalex.org/W1911851253","https://openalex.org/W2488480569","https://openalex.org/W1602531054","https://openalex.org/W2056600683","https://openalex.org/W4239999152","https://openalex.org/W2973191244","https://openalex.org/W2038428770","https://openalex.org/W1972943862","https://openalex.org/W4291198056","https://openalex.org/W2951738848"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,77],"new":[4],"recursive":[5,78,145],"algorithm":[6,123,139,149],"for":[7,33,62,95,106,113,180],"estimating":[8,96],"multichannel":[9],"autoregressive":[10],"(AR)":[11],"processes":[12],"in":[13],"spatially":[14],"correlated":[15],"noise":[16,47,98],"using":[17,126],"joint":[18],"extended":[19,75],"instrumental":[20],"variable":[21,86],"(EIV)":[22],"and":[23,41,71,100,129,150,182,188],"bias":[24],"compensation":[25],"(BC).":[26],"A":[27,57,91],"weighted":[28],"least":[29,54,146],"squares":[30,55,147],"solution":[31],"(WLS)":[32],"solving":[34,63],"the":[35,46,53,85,97,108,115,121,136,151,169,194,210],"Yule-Walker":[36],"(YW)":[37],"equations":[38],"from":[39,209],"EIV":[40],"BC":[42,109],"is":[43,50,60,73,124,166],"proposed,":[44],"while":[45],"covariance":[48],"parameters":[49,99],"estimated":[51],"via":[52,84],"method.":[56,153],"splitting":[58],"approach":[59],"proposed":[61,112,122,137,164],"this":[64],"WLS":[65],"problem":[66],"based":[67],"on":[68,176],"matrix":[69],"splitting,":[70],"it":[72],"further":[74],"to":[76,168,204],"algorithm,":[79],"which":[80],"can":[81,196],"be":[82,197],"solved":[83],"forgetting":[87],"factor":[88],"(VFF)-EIV":[89],"algorithm.":[90],"robust":[92],"smoothing":[93],"method":[94,105,165],"an":[101,205],"adaptive":[102],"model":[103],"selection":[104],"controlling":[107],"contribution":[110],"are":[111],"reducing":[114],"estimation":[116],"variance.":[117],"The":[118,163,186],"validity":[119],"of":[120],"evaluated":[125],"both":[127],"synthetic":[128],"real":[130],"data.":[131],"Experimental":[132],"results":[133],"show":[134],"that":[135],"VFF-EBC":[138],"gives":[140],"higher":[141],"accuracy":[142],"than":[143],"conventional":[144],"(RLS)":[148],"VFF-EIV":[152],"It":[154,200],"also":[155,202],"provides":[156],"faster":[157],"tracking":[158],"speed":[159],"under":[160],"sudden":[161],"changes.":[162],"applied":[167,203],"BCI":[170],"competition":[171],"IV-2b":[172],"EEG":[173],"data":[174,208],"set":[175],"motor":[177],"imagery":[178],"tasks":[179,195],"spectrum":[181],"effective":[183],"connectivity":[184],"estimation.":[185],"high-alpha":[187],"beta":[189],"event-related":[190],"desynchronization":[191],"associated":[192],"with":[193],"clearly":[198],"revealed.":[199],"was":[201],"auditory":[206],"odd-ball":[207],"Open-fMRI":[211],"database.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}