{"id":"https://openalex.org/W2891523369","doi":"https://doi.org/10.23919/icif.2018.8455538","title":"Variational Bayesian Inference for Jump Markov Linear Systems with Unknown Transition Probabilities","display_name":"Variational Bayesian Inference for Jump Markov Linear Systems with Unknown Transition Probabilities","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2891523369","doi":"https://doi.org/10.23919/icif.2018.8455538","mag":"2891523369"},"language":"en","primary_location":{"id":"doi:10.23919/icif.2018.8455538","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2018.8455538","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Information Fusion (FUSION)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5069829875","display_name":"Jingying Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingying Cao","raw_affiliation_strings":["School of Automation, Ministry of Education, Xi'an, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Ministry of Education, Xi'an, P. R. China","institution_ids":["https://openalex.org/I1327237609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100646875","display_name":"Yan Liang","orcid":"https://orcid.org/0000-0003-4798-4257"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Liang","raw_affiliation_strings":["School of Automation, Ministry of Education, Xi'an, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Ministry of Education, Xi'an, P. R. China","institution_ids":["https://openalex.org/I1327237609"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100786347","display_name":"Liwei Liu","orcid":"https://orcid.org/0000-0003-2164-1061"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liwei Liu","raw_affiliation_strings":["School of Automation, Ministry of Education, Xi'an, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Ministry of Education, Xi'an, P. R. China","institution_ids":["https://openalex.org/I1327237609"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1327237609"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2065","last_page":"2071"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11236","display_name":"Control Systems and Identification","score":0.9959999918937683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5085288286209106},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49935126304626465},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.49807024002075195},{"id":"https://openalex.org/keywords/jump","display_name":"Jump","score":0.49250444769859314},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.49048230051994324},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4831816256046295},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4579036235809326},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45468828082084656},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4441251754760742},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.41568922996520996},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.39494752883911133},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.38968080282211304},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2115822434425354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12706193327903748},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1038389801979065}],"concepts":[{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5085288286209106},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49935126304626465},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.49807024002075195},{"id":"https://openalex.org/C2780695682","wikidata":"https://www.wikidata.org/wiki/Q4005959","display_name":"Jump","level":2,"score":0.49250444769859314},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.49048230051994324},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4831816256046295},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4579036235809326},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45468828082084656},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4441251754760742},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.41568922996520996},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.39494752883911133},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.38968080282211304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2115822434425354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12706193327903748},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1038389801979065},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/icif.2018.8455538","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2018.8455538","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Information Fusion (FUSION)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W89016767","https://openalex.org/W97620058","https://openalex.org/W575122527","https://openalex.org/W1531532259","https://openalex.org/W1580124909","https://openalex.org/W1663973292","https://openalex.org/W1723619723","https://openalex.org/W1972988279","https://openalex.org/W1974915931","https://openalex.org/W1983191662","https://openalex.org/W1989879829","https://openalex.org/W1993079427","https://openalex.org/W2000721204","https://openalex.org/W2048614226","https://openalex.org/W2049633694","https://openalex.org/W2095376999","https://openalex.org/W2102716594","https://openalex.org/W2112986539","https://openalex.org/W2115916404","https://openalex.org/W2117853077","https://openalex.org/W2121712307","https://openalex.org/W2132036885","https://openalex.org/W2147020682","https://openalex.org/W2147375925","https://openalex.org/W2151433093","https://openalex.org/W2227207838","https://openalex.org/W2238582461","https://openalex.org/W2511190659","https://openalex.org/W3129711340","https://openalex.org/W6603641933","https://openalex.org/W6634825659","https://openalex.org/W6726183165","https://openalex.org/W7037644959"],"related_works":["https://openalex.org/W2351666715","https://openalex.org/W2757332726","https://openalex.org/W1967543778","https://openalex.org/W2382902960","https://openalex.org/W1660242800","https://openalex.org/W2379651310","https://openalex.org/W2113019827","https://openalex.org/W1541249122","https://openalex.org/W2413828414","https://openalex.org/W2367222340"],"abstract_inverted_index":{"Jump":[0],"Markov":[1,13],"linear":[2],"systems":[3],"(JMLSs)":[4],"switch":[5],"among":[6],"simpler":[7],"models":[8],"according":[9],"to":[10,39,87,109,122],"a":[11,58,81],"finite":[12],"chain,":[14],"whose":[15],"parameter,":[16],"namely":[17],"transition":[18,76],"probability":[19],"matrix":[20],"(TPM),":[21],"is":[22,52,85,107,125,135],"rarely":[23],"known":[24],"and":[25,54,56,69,95,119],"would":[26],"cause":[27],"significant":[28],"loss":[29],"in":[30,42],"performance":[31,131],"of":[32,66,75,92,132,140],"estimator":[33],"if":[34],"not":[35],"sufficient,":[36],"thus":[37],"needs":[38],"be":[40],"estimated":[41],"practice.":[43],"This":[44],"paper":[45],"considers":[46],"the":[47,73,88],"general":[48],"situation":[49],"where":[50],"TPM":[51],"unknown":[53,70],"random,":[55],"presents":[57],"variational":[59,82],"Bayesian":[60,83,111],"method":[61,106,134],"for":[62,117],"recursive":[63,105],"joint":[64,89],"estimation":[65,115],"system":[67,94],"state":[68,97,114],"TPM.":[71],"Under":[72],"assumption":[74],"probabilities":[77],"following":[78],"Dirichlet":[79],"distributions,":[80],"approximation":[84],"made":[86],"posterior":[90],"distribution":[91],"TPM,":[93],"modal":[96],"on":[98],"each":[99],"time":[100],"step":[101],"separately.":[102],"The":[103,130],"resulting":[104],"applicable":[108],"various":[110],"multiple":[112],"model":[113],"algorithms":[116],"JMLSs":[118],"an":[120,128],"application":[121],"IMM":[123],"algorithm":[124],"demonstrated":[126],"as":[127],"example.":[129],"proposed":[133],"illustrated":[136],"by":[137],"numerical":[138],"simulations":[139],"maneuvering":[141],"target":[142],"tracking.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}