{"id":"https://openalex.org/W4232653939","doi":"https://doi.org/10.1109/tsp.2016.2598324","title":"Sequential Estimation of Hidden ARMA Processes by Particle Filtering\u2014Part II","display_name":"Sequential Estimation of Hidden ARMA Processes by Particle Filtering\u2014Part II","publication_year":2016,"publication_date":"2016-08-04","ids":{"openalex":"https://openalex.org/W4232653939","doi":"https://doi.org/10.1109/tsp.2016.2598324"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2016.2598324","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2016.2598324","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","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/A5040717332","display_name":"I\u00f1igo Urteaga","orcid":"https://orcid.org/0000-0003-3656-0037"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Inigo Urteaga","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006962534","display_name":"Petar M. Djuri\u0107","orcid":"https://orcid.org/0000-0001-7791-3199"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Petar M. Djuric","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA","institution_ids":["https://openalex.org/I59553526"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5040717332"],"corresponding_institution_ids":["https://openalex.org/I59553526"],"apc_list":null,"apc_paid":null,"fwci":1.2854,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.88280356,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"65","issue":"2","first_page":"494","last_page":"504"},"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":0.9994000196456909,"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":0.9994000196456909,"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":0.998199999332428,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9958999752998352,"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/autoregressive\u2013moving-average-model","display_name":"Autoregressive\u2013moving-average model","score":0.8271987438201904},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.7923202514648438},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.67629075050354},{"id":"https://openalex.org/keywords/state-space-representation","display_name":"State-space representation","score":0.5909449458122253},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5771692991256714},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.5262336134910583},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5179575681686401},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.507733941078186},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.48436984419822693},{"id":"https://openalex.org/keywords/moving-average","display_name":"Moving average","score":0.4707432687282562},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4687402844429016},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.4537801742553711},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43811553716659546},{"id":"https://openalex.org/keywords/sequential-estimation","display_name":"Sequential estimation","score":0.41811931133270264},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4163272976875305},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2243264615535736},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20837253332138062},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1500779092311859}],"concepts":[{"id":"https://openalex.org/C74883015","wikidata":"https://www.wikidata.org/wiki/Q290467","display_name":"Autoregressive\u2013moving-average model","level":3,"score":0.8271987438201904},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.7923202514648438},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.67629075050354},{"id":"https://openalex.org/C52918065","wikidata":"https://www.wikidata.org/wiki/Q230945","display_name":"State-space representation","level":2,"score":0.5909449458122253},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5771692991256714},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.5262336134910583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5179575681686401},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.507733941078186},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.48436984419822693},{"id":"https://openalex.org/C175706884","wikidata":"https://www.wikidata.org/wiki/Q1130194","display_name":"Moving average","level":2,"score":0.4707432687282562},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4687402844429016},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.4537801742553711},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43811553716659546},{"id":"https://openalex.org/C86426650","wikidata":"https://www.wikidata.org/wiki/Q7452504","display_name":"Sequential estimation","level":2,"score":0.41811931133270264},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4163272976875305},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2243264615535736},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20837253332138062},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1500779092311859},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2016.2598324","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2016.2598324","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4443120474","display_name":null,"funder_award_id":"CCF-1320626","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W113895413","https://openalex.org/W1483307070","https://openalex.org/W1499861606","https://openalex.org/W1506414135","https://openalex.org/W1520710862","https://openalex.org/W1598813349","https://openalex.org/W1965943163","https://openalex.org/W2006866859","https://openalex.org/W2014730874","https://openalex.org/W2043078029","https://openalex.org/W2047554048","https://openalex.org/W2058815839","https://openalex.org/W2064517238","https://openalex.org/W2081741802","https://openalex.org/W2085157190","https://openalex.org/W2098091224","https://openalex.org/W2098613108","https://openalex.org/W2108755939","https://openalex.org/W2109965835","https://openalex.org/W2112007346","https://openalex.org/W2114160172","https://openalex.org/W2148061324","https://openalex.org/W2150642605","https://openalex.org/W2155739232","https://openalex.org/W2160337655","https://openalex.org/W2168175751","https://openalex.org/W2170621196","https://openalex.org/W2213039871","https://openalex.org/W2313953460","https://openalex.org/W2480874920","https://openalex.org/W2921430350","https://openalex.org/W3015420945","https://openalex.org/W3103934441","https://openalex.org/W3123857276","https://openalex.org/W4231057675","https://openalex.org/W4255133955","https://openalex.org/W4292963524","https://openalex.org/W6679042671","https://openalex.org/W7030535387"],"related_works":["https://openalex.org/W2036994430","https://openalex.org/W2413726729","https://openalex.org/W3190289737","https://openalex.org/W1985666753","https://openalex.org/W2384744720","https://openalex.org/W3021952245","https://openalex.org/W2367697829","https://openalex.org/W2900672867","https://openalex.org/W2333340489","https://openalex.org/W2904610199"],"abstract_inverted_index":{"This":[0],"is":[1],"Part":[2,28,65,177],"II":[3],"of":[4,7,15,42,49,72,84,88,127,137,163],"a":[5,32,91,112,117,147],"series":[6],"two":[8],"papers":[9],"where":[10,35,46],"we":[11,30,60,115],"address":[12],"sequential":[13],"estimation":[14],"wide-sense":[16],"stationary":[17],"autoregressive":[18],"moving":[19],"average":[20],"(ARMA)":[21],"state":[22,37,97,123,139],"processes":[23,81],"by":[24,67,98,110],"particle":[25,148],"filtering.":[26],"In":[27,57],"I,":[29],"considered":[31],"state-space":[33],"model":[34,109,130,143],"the":[36,47,50,69,75,79,96,107,122,125,129,134,138,155,161,164,174],"was":[38],"an":[39],"ARMA":[40,80,142],"process":[41,51],"known":[43,54],"order":[44],"and":[45,104,145,154,170],"parameters":[48],"could":[52],"be":[53],"or":[55],"unknown.":[56],"this":[58],"paper,":[59],"extend":[61],"our":[62],"work":[63],"from":[64,176],"I":[66],"considering":[68],"same":[70],"type":[71],"models,":[73,103],"with":[74,100,167,173],"added":[76],"complexity":[77],"that":[78,93,119,152],"are":[82],"now":[83],"unknown":[85,141],"order.":[86,131],"Instead":[87],"working":[89],"on":[90,151],"scheme":[92],"first":[94],"tracks":[95],"operating":[99],"different":[101],"assumed":[102],"then":[105],"selects":[106],"best":[108],"using":[111],"predefined":[113],"criterion,":[114],"present":[116],"method":[118,166],"directly":[120],"estimates":[121],"without":[124],"need":[126],"knowing":[128],"We":[132,159],"derive":[133],"transition":[135],"density":[136,153],"for":[140],"order,":[144],"propose":[146],"filter":[149],"based":[150],"empirical":[156],"Bayesian":[157],"methodology.":[158],"demonstrate":[160],"performance":[162],"proposed":[165],"computer":[168],"simulations":[169],"compare":[171],"it":[172],"methods":[175],"I.":[178]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}