{"id":"https://openalex.org/W1675167203","doi":"https://doi.org/10.1109/isit.2015.7282433","title":"Quickest change detection and Kullback-Leibler divergence for two-state hidden Markov models","display_name":"Quickest change detection and Kullback-Leibler divergence for two-state hidden Markov models","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1675167203","doi":"https://doi.org/10.1109/isit.2015.7282433","mag":"1675167203"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2015.7282433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2015.7282433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Symposium on Information Theory (ISIT)","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/A5032872987","display_name":"Cheng\u2013Der Fuh","orcid":"https://orcid.org/0000-0003-4174-528X"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Cheng-Der Fuh","raw_affiliation_strings":["Graduate Institute of Statistics, National Central University, Taiwan, ROC","Graduate Institute of Statistics, National Central University Taiwan, ROC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Statistics, National Central University, Taiwan, ROC","institution_ids":["https://openalex.org/I22265921"]},{"raw_affiliation_string":"Graduate Institute of Statistics, National Central University Taiwan, ROC","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005740286","display_name":"Yajun Mei","orcid":"https://orcid.org/0000-0002-1015-990X"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yajun Mei","raw_affiliation_strings":["School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, U.S.A","School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, 30332-0225, U.S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, U.S.A","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, 30332-0225, U.S.A","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"44","issue":null,"first_page":"141","last_page":"145"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9890000224113464,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9799000024795532,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.7787459492683411},{"id":"https://openalex.org/keywords/cusum","display_name":"CUSUM","score":0.6631953716278076},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.6431112885475159},{"id":"https://openalex.org/keywords/kullback\u2013leibler-divergence","display_name":"Kullback\u2013Leibler divergence","score":0.6214417219161987},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.523200273513794},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4830828011035919},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4662230312824249},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.45620062947273254},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.45046374201774597},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43793267011642456},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4155750274658203},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.35023319721221924},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2563320994377136},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24154812097549438}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.7787459492683411},{"id":"https://openalex.org/C178518018","wikidata":"https://www.wikidata.org/wiki/Q1024555","display_name":"CUSUM","level":2,"score":0.6631953716278076},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.6431112885475159},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.6214417219161987},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.523200273513794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4830828011035919},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4662230312824249},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.45620062947273254},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.45046374201774597},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43793267011642456},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4155750274658203},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.35023319721221924},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2563320994377136},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24154812097549438},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit.2015.7282433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2015.7282433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Symposium on Information Theory (ISIT)","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":15,"referenced_works":["https://openalex.org/W1965662339","https://openalex.org/W1967128863","https://openalex.org/W1981904416","https://openalex.org/W1999428284","https://openalex.org/W2002644365","https://openalex.org/W2004094275","https://openalex.org/W2018319586","https://openalex.org/W2051903196","https://openalex.org/W2112072995","https://openalex.org/W2126099188","https://openalex.org/W2145997363","https://openalex.org/W2152321560","https://openalex.org/W2166426063","https://openalex.org/W2325067522","https://openalex.org/W3105579973"],"related_works":["https://openalex.org/W2105425943","https://openalex.org/W4307934096","https://openalex.org/W2910753852","https://openalex.org/W4390691386","https://openalex.org/W2115962466","https://openalex.org/W2105321464","https://openalex.org/W2887774187","https://openalex.org/W2388220555","https://openalex.org/W1554844486","https://openalex.org/W1520875569"],"abstract_inverted_index":{"The":[0],"quickest":[1],"change":[2,22,44],"detection":[3],"problem":[4],"is":[5,68],"studied":[6],"in":[7,94,123],"two-state":[8,160],"hidden":[9],"Markov":[10],"models":[11],"(HMM),":[12],"where":[13],"the":[14,19,42,51,59,73,83,89,115,129,137,155,163,168],"vector":[15],"parameter":[16,131],"\u03b8":[17,24,29,132],"of":[18,136,159],"HMM":[20,138],"may":[21],"from":[23],"<sub":[25,30,133],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[26,31,134],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">0</sub>":[27],"to":[28,40,118],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[32,135],"at":[33],"some":[34,107],"unknown":[35],"time,":[36],"and":[37,167],"one":[38],"wants":[39],"detect":[41],"true":[43],"as":[45,47,102],"quickly":[46],"possible":[48],"while":[49,65],"controlling":[50],"false":[52],"alarm":[53],"rate.":[54],"It":[55],"turns":[56],"out":[57],"that":[58,88,151],"generalized":[60],"likelihood":[61],"ratio":[62],"(GLR)":[63],"scheme,":[64],"theoretically":[66],"straightforward,":[67],"generally":[69],"computationally":[70,79],"infeasible":[71],"for":[72,82,106],"HMM.":[74],"To":[75],"develop":[76],"efficient":[77],"but":[78],"simple":[80],"schemes":[81,122],"HMM,":[84],"we":[85,113],"first":[86],"show":[87],"recursive":[90,120],"CUSUM":[91],"scheme":[92,105],"proposed":[93],"Fuh":[95],"(Ann.":[96],"Statist.,":[97],"2003)":[98],"can":[99,152],"be":[100],"regarded":[101],"a":[103,124,140],"quasi-GLR":[104,116],"suitable":[108],"pseudo":[109],"post-change":[110,130],"hypotheses.":[111],"Next,":[112],"extend":[114],"idea":[117],"propose":[119],"score":[121],"more":[125],"complicated":[126],"scenario":[127],"when":[128],"involves":[139],"real-valued":[141],"nuisance":[142],"parameter.":[143],"Finally,":[144],"our":[145],"research":[146],"provides":[147],"an":[148],"alternative":[149],"approach":[150],"numerically":[153],"compute":[154],"Kullback-Leibler":[156],"(KL)":[157],"divergence":[158],"HMMs":[161],"via":[162],"invariant":[164],"probability":[165],"measure":[166],"Fredholm":[169],"integral":[170],"equation.":[171]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
