{"id":"https://openalex.org/W1999577353","doi":"https://doi.org/10.1109/lsp.2014.2305115","title":"The Marginal Enumeration Bayesian Cram\u00e9r\u2013Rao Bound for Jump Markov Systems","display_name":"The Marginal Enumeration Bayesian Cram\u00e9r\u2013Rao Bound for Jump Markov Systems","publication_year":2014,"publication_date":"2014-02-07","ids":{"openalex":"https://openalex.org/W1999577353","doi":"https://doi.org/10.1109/lsp.2014.2305115","mag":"1999577353"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2014.2305115","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2014.2305115","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":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-105741","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000005967","display_name":"Carsten Fritsche","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carsten Fritsche","raw_affiliation_strings":["IFEN GmbH, Poing, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IFEN GmbH, Poing, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052094664","display_name":"Umut Orguner","orcid":"https://orcid.org/0000-0002-7670-5635"},"institutions":[{"id":"https://openalex.org/I201799495","display_name":"Middle East Technical University","ror":"https://ror.org/014weej12","country_code":"TR","type":"education","lineage":["https://openalex.org/I201799495"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Umut Orguner","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey","Dept. of Electr. & Electron. Eng., Middle East Tech. Univ., Ankara, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey","institution_ids":["https://openalex.org/I201799495"]},{"raw_affiliation_string":"Dept. of Electr. & Electron. Eng., Middle East Tech. Univ., Ankara, Turkey","institution_ids":["https://openalex.org/I201799495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029413988","display_name":"Lennart Svensson","orcid":"https://orcid.org/0000-0003-0206-9186"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Lennart Svensson","raw_affiliation_strings":["Department of Signals and Systems, Chalmers University of Technology, G\u00f6teborg, Sweden","Dept. of Signals and Systems, Chalmers Univ. of Technology, G\u00f6teborg, Sweden#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signals and Systems, Chalmers University of Technology, G\u00f6teborg, Sweden","institution_ids":["https://openalex.org/I66862912"]},{"raw_affiliation_string":"Dept. of Signals and Systems, Chalmers Univ. of Technology, G\u00f6teborg, Sweden#TAB#","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058002446","display_name":"Fredrik Gustafsson","orcid":"https://orcid.org/0000-0003-3270-171X"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Fredrik Gustafsson","raw_affiliation_strings":["Department of Electrical Engineering, Link\u00f6ping University, Link\u00f6ping, Sweden","Dept. of Electr. Eng. Linkoping Univ. Link\u00f6ping Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Link\u00f6ping University, Link\u00f6ping, Sweden","institution_ids":["https://openalex.org/I102134673"]},{"raw_affiliation_string":"Dept. of Electr. Eng. Linkoping Univ. Link\u00f6ping Sweden","institution_ids":["https://openalex.org/I102134673"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8284,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.80250466,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"21","issue":"4","first_page":"464","last_page":"468"},"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":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","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/T10876","display_name":"Fault Detection and Control Systems","score":0.9973000288009644,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9965000152587891,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/enumeration","display_name":"Enumeration","score":0.7191247940063477},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6991876363754272},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.6622951626777649},{"id":"https://openalex.org/keywords/jump","display_name":"Jump","score":0.6069487929344177},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5899798274040222},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5638560056686401},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5475314259529114},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5329455137252808},{"id":"https://openalex.org/keywords/marginal-likelihood","display_name":"Marginal likelihood","score":0.4646928012371063},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.42240017652511597},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4029274880886078},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.37497979402542114},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36225706338882446},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3477741777896881},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.25950899720191956}],"concepts":[{"id":"https://openalex.org/C156340839","wikidata":"https://www.wikidata.org/wiki/Q2704791","display_name":"Enumeration","level":2,"score":0.7191247940063477},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6991876363754272},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.6622951626777649},{"id":"https://openalex.org/C2780695682","wikidata":"https://www.wikidata.org/wiki/Q4005959","display_name":"Jump","level":2,"score":0.6069487929344177},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5899798274040222},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5638560056686401},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5475314259529114},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5329455137252808},{"id":"https://openalex.org/C95923904","wikidata":"https://www.wikidata.org/wiki/Q6760420","display_name":"Marginal likelihood","level":3,"score":0.4646928012371063},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.42240017652511597},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4029274880886078},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.37497979402542114},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36225706338882446},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3477741777896881},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.25950899720191956},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/lsp.2014.2305115","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2014.2305115","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"},{"id":"pmh:oai:DiVA.org:liu-105741","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-105741","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:open.metu.edu.tr:11511/32845","is_oa":true,"landing_page_url":"https://hdl.handle.net/11511/32845","pdf_url":null,"source":{"id":"https://openalex.org/S4306402495","display_name":"OpenMETU (Middle East Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I201799495","host_organization_name":"Middle East Technical University","host_organization_lineage":["https://openalex.org/I201799495"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},{"id":"pmh:oai:publications.lib.chalmers.se:196350","is_oa":false,"landing_page_url":"http://publications.lib.chalmers.se/publication/196350-the-marginal-enumeration-bayesian-cramer-rao-bound-for-jump-markov-systems","pdf_url":null,"source":{"id":"https://openalex.org/S4377196470","display_name":"Chalmers Publication Library (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text.Article.Journal.PeerReviewed"},{"id":"pmh:oai:research.chalmers.se:196350","is_oa":false,"landing_page_url":"https://research.chalmers.se/en/publication/196350","pdf_url":null,"source":{"id":"https://openalex.org/S4306402469","display_name":"Chalmers Research (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null}],"best_oa_location":{"id":"pmh:oai:DiVA.org:liu-105741","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-105741","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1483307070","https://openalex.org/W1490978409","https://openalex.org/W1513008779","https://openalex.org/W1517926209","https://openalex.org/W1531532259","https://openalex.org/W1536252645","https://openalex.org/W1984197955","https://openalex.org/W1987615302","https://openalex.org/W2077305791","https://openalex.org/W2090562304","https://openalex.org/W2104130465","https://openalex.org/W2104232570","https://openalex.org/W2111241854","https://openalex.org/W2114690521","https://openalex.org/W2117397690","https://openalex.org/W2121712307","https://openalex.org/W2123211114","https://openalex.org/W2125514280","https://openalex.org/W2128519721","https://openalex.org/W2143180486","https://openalex.org/W2148856141","https://openalex.org/W2159554537","https://openalex.org/W2162182236","https://openalex.org/W2502276222","https://openalex.org/W2565753657","https://openalex.org/W3124515326","https://openalex.org/W4214753641"],"related_works":["https://openalex.org/W1980576599","https://openalex.org/W2127518758","https://openalex.org/W4248699874","https://openalex.org/W2128702080","https://openalex.org/W3037174382","https://openalex.org/W3198596521","https://openalex.org/W2392311667","https://openalex.org/W2069074906","https://openalex.org/W2380172021","https://openalex.org/W1999577353"],"abstract_inverted_index":{"A":[0],"marginal":[1],"version":[2],"of":[3,37],"the":[4,20,31,38],"enumeration":[5],"Bayesian":[6],"Cram\u00e9r-Rao":[7],"Bound":[8],"(EBCRB)":[9],"for":[10],"jump":[11],"Markov":[12],"systems":[13],"is":[14,17,23,43],"proposed.":[15],"It":[16],"shown":[18],"that":[19],"proposed":[21],"bound":[22,42],"at":[24],"least":[25],"as":[26,28],"tight":[27],"EBCRB":[29,52],"and":[30,51],"improvement":[32],"stems":[33],"from":[34],"better":[35],"handling":[36],"nonlinearities.":[39],"The":[40],"new":[41],"illustrated":[44],"to":[45],"yield":[46],"tighter":[47],"results":[48],"than":[49],"BCRB":[50],"on":[53],"a":[54],"benchmark":[55],"example.":[56]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}