{"id":"https://openalex.org/W2903357735","doi":"https://doi.org/10.23919/eusipco.2018.8553415","title":"Identification of Multichannel AR Models with Additive Noise: a Frisch Scheme Approach","display_name":"Identification of Multichannel AR Models with Additive Noise: a Frisch Scheme Approach","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2903357735","doi":"https://doi.org/10.23919/eusipco.2018.8553415","mag":"2903357735"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2018.8553415","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553415","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","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/A5037192604","display_name":"Roberto Diversi","orcid":"https://orcid.org/0000-0002-4033-4019"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Roberto Diversi","raw_affiliation_strings":["Department of Electrical, University of Bologna, Bologna, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Electrical, University of Bologna, Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5037192604"],"corresponding_institution_ids":["https://openalex.org/I9360294"],"apc_list":null,"apc_paid":null,"fwci":0.1839,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.52442736,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1252","last_page":"1256"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11236","display_name":"Control Systems and Identification","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/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":0.9976999759674072,"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/identification","display_name":"Identification (biology)","score":0.6615117192268372},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6067826747894287},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5963261723518372},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5719804763793945},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3879459500312805},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38287463784217834},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28272250294685364},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22314190864562988}],"concepts":[{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6615117192268372},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6067826747894287},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5963261723518372},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5719804763793945},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3879459500312805},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38287463784217834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28272250294685364},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22314190864562988},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.23919/eusipco.2018.8553415","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553415","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},{"id":"pmh:oai:cris.unibo.it:11585/668711","is_oa":false,"landing_page_url":"http://hdl.handle.net/11585/668711","pdf_url":null,"source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W210359992","https://openalex.org/W229723314","https://openalex.org/W1578369397","https://openalex.org/W1654016072","https://openalex.org/W1966969760","https://openalex.org/W1981181101","https://openalex.org/W1982139997","https://openalex.org/W1985963135","https://openalex.org/W1988891592","https://openalex.org/W1995536493","https://openalex.org/W2000326072","https://openalex.org/W2040739698","https://openalex.org/W2042179126","https://openalex.org/W2048413940","https://openalex.org/W2054515467","https://openalex.org/W2069300914","https://openalex.org/W2091683338","https://openalex.org/W2105967858","https://openalex.org/W2106258988","https://openalex.org/W2107896723","https://openalex.org/W2111105339","https://openalex.org/W2118771073","https://openalex.org/W2126810361","https://openalex.org/W2171419871","https://openalex.org/W2404594948","https://openalex.org/W2504952917","https://openalex.org/W2520654854","https://openalex.org/W2614842316","https://openalex.org/W4302770171","https://openalex.org/W4309573086","https://openalex.org/W6634698814","https://openalex.org/W6713165434"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2053286651","https://openalex.org/W1975289146","https://openalex.org/W2181743346","https://openalex.org/W2187401768","https://openalex.org/W2181413294","https://openalex.org/W2052122378","https://openalex.org/W2105887828","https://openalex.org/W2372764048"],"abstract_inverted_index":{"A":[0],"new":[1],"approach":[2],"for":[3],"estimating":[4],"multichannel":[5],"AR":[6],"(M-AR)":[7],"models":[8],"from":[9,99],"noisy":[10,45,93],"observations":[11],"is":[12,57,78],"proposed.":[13],"It":[14],"relies":[15],"on":[16,80],"the":[17,26,29,39,44,49,76,81,84,89,92,100,113],"so-called":[18],"Frisch":[19],"scheme,":[20],"whose":[21],"rationale":[22],"consists":[23],"in":[24,65,75],"finding":[25],"solution":[27],"of":[28,35,43,51,83,88,91,107],"identification":[30],"problem":[31],"within":[32],"a":[33,61,69],"locus":[34,50],"solutions":[36,52],"compatible":[37],"with":[38,96],"second":[40],"order":[41,66],"statistics":[42],"data.":[46,101],"Once":[47],"that":[48,112],"has":[53],"been":[54],"defined,":[55],"it":[56],"necessary":[58],"to":[59,67],"introduce":[60],"suitable":[62],"selection":[63],"criterion":[64,73],"identify":[68],"single":[70],"solution.":[71],"The":[72,102],"proposed":[74,114],"paper":[77],"based":[79],"comparison":[82],"theoretical":[85],"statistical":[86],"properties":[87],"residual":[90],"M-AR":[94],"model":[95],"those":[97],"computed":[98],"results":[103],"obtained":[104],"by":[105],"means":[106],"Monte":[108],"Carlo":[109],"simulations":[110],"show":[111],"algorithm":[115],"outperforms":[116],"some":[117],"existing":[118],"methods.":[119]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
