{"id":"https://openalex.org/W4414079806","doi":"https://doi.org/10.1109/lsp.2025.3607235","title":"Bayesian Transfer Filtering via UFIR Adaptive Regularization","display_name":"Bayesian Transfer Filtering via UFIR Adaptive Regularization","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414079806","doi":"https://doi.org/10.1109/lsp.2025.3607235"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2025.3607235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3607235","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5116592751","display_name":"Tianyu Zhang","orcid":"https://orcid.org/0000-0003-1471-8323"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyu Zhang","raw_affiliation_strings":["Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, China"],"raw_orcid":"https://orcid.org/0000-0003-1471-8323","affiliations":[{"raw_affiliation_string":"Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007377543","display_name":"Xiaojing Ping","orcid":"https://orcid.org/0000-0002-0801-0110"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojing Ping","raw_affiliation_strings":["Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, China"],"raw_orcid":"https://orcid.org/0000-0002-0801-0110","affiliations":[{"raw_affiliation_string":"Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023417619","display_name":"Shunyi Zhao","orcid":"https://orcid.org/0000-0001-5363-8305"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shunyi Zhao","raw_affiliation_strings":["Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, China"],"raw_orcid":"https://orcid.org/0000-0001-5363-8305","affiliations":[{"raw_affiliation_string":"Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058205797","display_name":"Yuriy S. Shmaliy","orcid":"https://orcid.org/0000-0001-6848-453X"},"institutions":[{"id":"https://openalex.org/I129858807","display_name":"Universidad de Guanajuato","ror":"https://ror.org/058cjye32","country_code":"MX","type":"education","lineage":["https://openalex.org/I129858807"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Yuriy S. Shmaliy","raw_affiliation_strings":["Department of Electronics Engineering, Universidad de Guanajuato, Salamanca, Mexico"],"raw_orcid":"https://orcid.org/0000-0001-6848-453X","affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Universidad de Guanajuato, Salamanca, Mexico","institution_ids":["https://openalex.org/I129858807"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20442649,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"32","issue":null,"first_page":"3630","last_page":"3634"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9677000045776367,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9677000045776367,"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"}},{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9552000164985657,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12537","display_name":"Flow Measurement and Analysis","score":0.9521999955177307,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/interpretability","display_name":"Interpretability","score":0.7390999794006348},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6187000274658203},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5562999844551086},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.4975999891757965},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.4925000071525574},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4156999886035919},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.36419999599456787},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.36419999599456787},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.357699990272522}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7390999794006348},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6187000274658203},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6029000282287598},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5562999844551086},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.4975999891757965},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.4925000071525574},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48100000619888306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.474700003862381},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4156999886035919},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.36419999599456787},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.36419999599456787},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3596999943256378},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.357699990272522},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.3411000072956085},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.3391999900341034},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.3352999985218048},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C13107197","wikidata":"https://www.wikidata.org/wiki/Q6394192","display_name":"Kernel adaptive filter","level":4,"score":0.3138999938964844},{"id":"https://openalex.org/C198386975","wikidata":"https://www.wikidata.org/wiki/Q117785","display_name":"Finite impulse response","level":2,"score":0.31209999322891235},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.3012000024318695},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29899999499320984},{"id":"https://openalex.org/C41614226","wikidata":"https://www.wikidata.org/wiki/Q5449244","display_name":"Filtering problem","level":4,"score":0.2939000129699707},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2896000146865845},{"id":"https://openalex.org/C81299745","wikidata":"https://www.wikidata.org/wiki/Q334269","display_name":"Transfer function","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C139722471","wikidata":"https://www.wikidata.org/wiki/Q2619517","display_name":"Linear filter","level":3,"score":0.26570001244544983},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.26460000872612},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C40343088","wikidata":"https://www.wikidata.org/wiki/Q3059012","display_name":"Recursive Bayesian estimation","level":3,"score":0.2535000145435333},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.2535000145435333},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2025.3607235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3607235","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7415444703","display_name":null,"funder_award_id":"62373167","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2595724236","https://openalex.org/W2773192101","https://openalex.org/W2899407767","https://openalex.org/W2967548573","https://openalex.org/W2993595083","https://openalex.org/W3090170406","https://openalex.org/W3181494251","https://openalex.org/W3201459702","https://openalex.org/W4285494028","https://openalex.org/W4285598347","https://openalex.org/W4286633044","https://openalex.org/W4312816360","https://openalex.org/W4385871710","https://openalex.org/W4386590925","https://openalex.org/W4391020732","https://openalex.org/W4391421261","https://openalex.org/W4402123878","https://openalex.org/W4404469668","https://openalex.org/W4406727888","https://openalex.org/W4411336556"],"related_works":["https://openalex.org/W4254199101","https://openalex.org/W4300427796","https://openalex.org/W2384522253","https://openalex.org/W1670153145","https://openalex.org/W4232526067","https://openalex.org/W2439220085","https://openalex.org/W2051864124","https://openalex.org/W3023929447","https://openalex.org/W2021131614","https://openalex.org/W2127076901"],"abstract_inverted_index":{"The":[0],"Bayesian":[1,29,68],"approach":[2],"resulting":[3],"in":[4,108],"the":[5,40,53,57,61,66,74,79,91,98,121,124],"Kalman":[6],"filter":[7],"(KF),":[8],"often":[9],"struggle":[10],"with":[11],"model":[12],"uncertainties,":[13],"particularly":[14],"when":[15],"noise":[16,129],"statistics":[17],"are":[18],"inaccurate.":[19],"Inspired":[20],"by":[21,38],"transfer":[22,30,111],"learning,":[23],"this":[24,85],"letter":[25],"presents":[26],"a":[27,105],"novel":[28],"filtering":[31,55],"framework":[32,126],"that":[33,84],"significantly":[34],"enhances":[35],"estimation":[36],"accuracy":[37],"incorporating":[39],"unbiased":[41],"finite":[42],"impulse":[43],"response":[44],"(UFIR)":[45],"structure":[46],"for":[47,100],"adaptive":[48,86],"regularization.":[49],"To":[50],"adaptively":[51],"adjust":[52],"UFIR":[54],"estimate,":[56],"statistical":[58],"significance":[59],"of":[60,123],"transfer-regularization":[62],"is":[63,70,82,104],"learned":[64],"and":[65,93,115],"variational":[67],"method":[69],"applied":[71],"to":[72],"learn":[73],"regularization":[75],"factor":[76],"directly":[77],"from":[78],"data.":[80],"It":[81],"shown":[83],"strategy":[87],"not":[88],"only":[89],"improves":[90],"interpretability":[92],"transferability":[94],"but":[95],"also":[96],"removes":[97],"need":[99],"heuristic":[101],"selection,":[102],"which":[103],"common":[106],"limitation":[107],"traditional":[109],"regularization-based":[110],"methods.":[112],"Numerical":[113],"simulations":[114],"water":[116],"tank":[117],"experiments":[118],"collectively":[119],"confirm":[120],"effectiveness":[122],"proposed":[125],"under":[127],"uncertain":[128],"statistics.":[130]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}