{"id":"https://openalex.org/W7131107407","doi":"https://doi.org/10.1109/jiot.2026.3667144","title":"Distributed Incremental Saturation Kernel-Based Correntropy Filter Subject to Unknown Non-Gaussian Noise and Measurement Bias","display_name":"Distributed Incremental Saturation Kernel-Based Correntropy Filter Subject to Unknown Non-Gaussian Noise and Measurement Bias","publication_year":2026,"publication_date":"2026-02-23","ids":{"openalex":"https://openalex.org/W7131107407","doi":"https://doi.org/10.1109/jiot.2026.3667144"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2026.3667144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3667144","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","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/A5064516775","display_name":"Jingang Liu","orcid":"https://orcid.org/0000-0001-9523-3402"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingang Liu","raw_affiliation_strings":["Center for Control Theory and Guidance Technology, Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0001-9523-3402","affiliations":[{"raw_affiliation_string":"Center for Control Theory and Guidance Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001526404","display_name":"Shenmin Song","orcid":"https://orcid.org/0000-0003-3177-6701"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenmin Song","raw_affiliation_strings":["Center for Control Theory and Guidance Technology, Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0003-3177-6701","affiliations":[{"raw_affiliation_string":"Center for Control Theory and Guidance Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":5.2933,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92321612,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"13","issue":"10","first_page":"21401","last_page":"21410"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.6492000222206116,"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"}},"topics":[{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.6492000222206116,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.035100001841783524,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12564","display_name":"Sensor Technology and Measurement Systems","score":0.03440000116825104,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/estimator","display_name":"Estimator","score":0.5752000212669373},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.52920001745224},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5134999752044678},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.453000009059906},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.42750000953674316},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.424699991941452},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.4171999990940094},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4108999967575073},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3781999945640564}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5752000212669373},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5702999830245972},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5680999755859375},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.52920001745224},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5134999752044678},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.453000009059906},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.42750000953674316},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.424699991941452},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.4171999990940094},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38850000500679016},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3781999945640564},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.3691999912261963},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3540000021457672},{"id":"https://openalex.org/C49344536","wikidata":"https://www.wikidata.org/wiki/Q726441","display_name":"Cauchy distribution","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.3321000039577484},{"id":"https://openalex.org/C19619285","wikidata":"https://www.wikidata.org/wiki/Q196372","display_name":"Observational error","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.303600013256073},{"id":"https://openalex.org/C13107197","wikidata":"https://www.wikidata.org/wiki/Q6394192","display_name":"Kernel adaptive filter","level":4,"score":0.30219998955726624},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2969000041484833},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.2928999960422516},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2874000072479248},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C9930424","wikidata":"https://www.wikidata.org/wiki/Q7426587","display_name":"Saturation (graph theory)","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.26330000162124634},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2621000111103058}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2026.3667144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3667144","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W2024307985","https://openalex.org/W2054091988","https://openalex.org/W2101051269","https://openalex.org/W2116564195","https://openalex.org/W2155963412","https://openalex.org/W2158191982","https://openalex.org/W2169329579","https://openalex.org/W2501182657","https://openalex.org/W2513248895","https://openalex.org/W2592448769","https://openalex.org/W2603428934","https://openalex.org/W2770746583","https://openalex.org/W2900245935","https://openalex.org/W2963134661","https://openalex.org/W3014813965","https://openalex.org/W3085837751","https://openalex.org/W3110908921","https://openalex.org/W3176679221","https://openalex.org/W3185589277","https://openalex.org/W3199423073","https://openalex.org/W3206469347","https://openalex.org/W4226177187","https://openalex.org/W4285200808","https://openalex.org/W4293523204","https://openalex.org/W4294869285","https://openalex.org/W4313022646","https://openalex.org/W4317103712","https://openalex.org/W4366169388","https://openalex.org/W4380986137","https://openalex.org/W4391892566","https://openalex.org/W4399142112","https://openalex.org/W4402668952","https://openalex.org/W4403446498","https://openalex.org/W4404630779","https://openalex.org/W4404688249","https://openalex.org/W4408145495","https://openalex.org/W4413785562"],"related_works":[],"abstract_inverted_index":{"In":[0,135],"this":[1],"paper,":[2],"a":[3,26,106],"distributed":[4],"incremental":[5,54,80,88,93],"saturation":[6,27,94,102],"correntropy":[7,95,103],"filter":[8,96],"is":[9,34,57,75,97,122],"proposed":[10,144,166],"for":[11],"multi-sensor":[12],"network":[13],"under":[14,149],"unknown":[15,66,87],"non-Gaussian":[16,24],"noise":[17,72,89],"and":[18,36,48,140,162],"measurement":[19,55,67,81],"bias.":[20,68],"First,":[21],"to":[22,63,112,125],"suppress":[23],"noise,":[25],"kernel":[28,50],"function":[29],"with":[30,105],"nonlinear":[31],"compression":[32],"characteristics":[33],"developed,":[35],"its":[37],"properties":[38],"are":[39,146],"investigated.":[40],"It":[41],"combines":[42],"the":[43,60,65,79,92,100,127,131,137,143,153,160,165],"benefits":[44],"of":[45,86,130,142,156,164],"both":[46],"Gaussian":[47],"Cauchy":[49],"functions.":[51],"Second,":[52],"an":[53,70],"equation":[56],"constructed":[58],"by":[59,99],"difference":[61],"method":[62],"eliminate":[64],"Concurrently,":[69],"adaptive":[71],"variance":[73],"estimator":[74],"designed":[76],"based":[77],"on":[78],"innovation,":[82],"enabling":[83],"real-time":[84],"estimation":[85,129],"variance.":[90],"Subsequently,":[91],"derived":[98],"presented":[101],"criterion,":[104],"dynamic":[107],"parameter":[108,114],"adjustment":[109],"strategy":[110],"introduced":[111],"mitigate":[113],"selection":[115],"uncertainty.":[116],"The":[117],"improved":[118],"covariance":[119],"intersection":[120],"technique":[121],"then":[123],"employed":[124],"achieve":[126],"consensus":[128],"whole":[132],"sensor":[133],"network.":[134],"addition,":[136],"unbiasedness,":[138],"boundedness":[139],"convergence":[141],"algorithms":[145],"rigorously":[147],"established":[148],"appropriate":[150],"conditions.":[151],"Finally,":[152],"simulation":[154],"results":[155],"three":[157],"scenarios":[158],"demonstrate":[159],"effectiveness":[161],"superiority":[163],"algorithms.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2026-02-24T00:00:00"}