{"id":"https://openalex.org/W2214499963","doi":"https://doi.org/10.1109/icassp.2016.7472454","title":"Distributed estimation of latent parameters in state space models using separable likelihoods","display_name":"Distributed estimation of latent parameters in state space models using separable likelihoods","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2214499963","doi":"https://doi.org/10.1109/icassp.2016.7472454","mag":"2214499963"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7472454","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472454","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.research.ed.ac.uk/en/publications/75adbf5b-838f-47de-b5b1-2063ad277cf7","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090912186","display_name":"Murat \u00dcney","orcid":"https://orcid.org/0000-0001-6561-0406"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Murat Uney","raw_affiliation_strings":["IDCOM, University of Edinburgh, Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"IDCOM, University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076320344","display_name":"B. Mulgrew","orcid":"https://orcid.org/0000-0002-8082-2818"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Bernard Mulgrew","raw_affiliation_strings":["IDCOM, University of Edinburgh, Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"IDCOM, University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074908755","display_name":"Daniel E. Clark","orcid":"https://orcid.org/0000-0002-0218-7994"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Daniel Clark","raw_affiliation_strings":["School of Eng. & Physical Sciences, Heriot-Watt University, Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"School of Eng. & Physical Sciences, Heriot-Watt University, Edinburgh, UK","institution_ids":["https://openalex.org/I32062511"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5090912186"],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":0.4417,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.77629786,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"7336","issue":null,"first_page":"4129","last_page":"4133"},"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":0.9980999827384949,"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":0.9980999827384949,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9868999719619751,"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/T10320","display_name":"Neural Networks and Applications","score":0.9684000015258789,"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/computer-science","display_name":"Computer science","score":0.6956488490104675},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6646789312362671},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5143674612045288},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.48700839281082153},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.4862159788608551},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.4736821949481964},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4723193347454071},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4539657533168793},{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.43296974897384644},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3468005061149597},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31904661655426025},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15815934538841248},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.10538512468338013},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.09012004733085632}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6956488490104675},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6646789312362671},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5143674612045288},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.48700839281082153},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.4862159788608551},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.4736821949481964},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4723193347454071},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4539657533168793},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.43296974897384644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3468005061149597},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31904661655426025},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15815934538841248},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.10538512468338013},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.09012004733085632},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icassp.2016.7472454","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472454","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.ed.ac.uk:openaire/75adbf5b-838f-47de-b5b1-2063ad277cf7","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/75adbf5b-838f-47de-b5b1-2063ad277cf7","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Uney, M, Mulgrew, B & Clark, D 2016, 'Distributed estimation of latent parameters in state space models using separable likelihoods', Paper presented at 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016, Shanghai, China, 20/03/16 - 25/03/16.","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:eprints.soton.ac.uk:475510","is_oa":false,"landing_page_url":"https://eprints.soton.ac.uk/475510/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401019","display_name":"ePrints Soton (University of Southampton)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I43439940","host_organization_name":"University of Southampton","host_organization_lineage":["https://openalex.org/I43439940"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"},{"id":"pmh:oai:pure.ed.ac.uk:publications/75adbf5b-838f-47de-b5b1-2063ad277cf7","is_oa":false,"landing_page_url":"https://www.research.ed.ac.uk/portal/en/publications/distributed-estimation-of-latent-parameters-in-state-space-models-using-separable-likelihoods(75adbf5b-838f-47de-b5b1-2063ad277cf7).html","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"pmh:oai:pure.ed.ac.uk:openaire/75adbf5b-838f-47de-b5b1-2063ad277cf7","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/75adbf5b-838f-47de-b5b1-2063ad277cf7","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Uney, M, Mulgrew, B & Clark, D 2016, 'Distributed estimation of latent parameters in state space models using separable likelihoods', Paper presented at 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016, Shanghai, China, 20/03/16 - 25/03/16.","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2327784722","display_name":null,"funder_award_id":"EP/J015180/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8726282573","display_name":null,"funder_award_id":"EP/K014277/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W159153715","https://openalex.org/W1987334239","https://openalex.org/W2004885217","https://openalex.org/W2019599312","https://openalex.org/W2027772285","https://openalex.org/W2033181272","https://openalex.org/W2040398233","https://openalex.org/W2044343239","https://openalex.org/W2055936398","https://openalex.org/W2073782198","https://openalex.org/W2076037741","https://openalex.org/W2081739442","https://openalex.org/W2098091224","https://openalex.org/W2099111195","https://openalex.org/W2103227205","https://openalex.org/W2110407935","https://openalex.org/W2112563055","https://openalex.org/W2118388220","https://openalex.org/W2120340025","https://openalex.org/W2137922573","https://openalex.org/W2152001538","https://openalex.org/W2154659203","https://openalex.org/W2251576751","https://openalex.org/W2293128770","https://openalex.org/W2592951924","https://openalex.org/W2744689969","https://openalex.org/W2951881983","https://openalex.org/W3103934441","https://openalex.org/W4293052541","https://openalex.org/W4316253766","https://openalex.org/W6655383422","https://openalex.org/W6676597516","https://openalex.org/W6691435420","https://openalex.org/W6697234987"],"related_works":["https://openalex.org/W4321064619","https://openalex.org/W2009525028","https://openalex.org/W3011179836","https://openalex.org/W2962925412","https://openalex.org/W2023672523","https://openalex.org/W4246719751","https://openalex.org/W2483165346","https://openalex.org/W2053599029","https://openalex.org/W2057373567","https://openalex.org/W1599711819"],"abstract_inverted_index":{"Motivated":[0],"by":[1],"object":[2],"tracking":[3,90],"applications":[4],"with":[5,48,57,73],"networked":[6],"sensors,":[7],"we":[8],"consider":[9],"multi":[10],"sensor":[11,123,131],"state":[12,118],"space":[13],"models.":[14],"Estimation":[15],"of":[16,33,35,41,51,109,117],"latent":[17],"parameters":[18],"in":[19,46,68,89,98,129],"these":[20,84],"models":[21,77],"requires":[22],"centralisation":[23,67],"because":[24],"the":[25,30,36,49,64,103,106,110,115],"parameter":[26],"likelihood":[27,69],"depend":[28],"on":[29,121],"measurement":[31],"histories":[32,43],"all":[34],"sensors.":[37,52],"Consequently,":[38],"joint":[39],"processing":[40],"multiple":[42],"pose":[44],"difficulties":[45],"scaling":[47],"number":[50],"We":[53,101,125],"propose":[54],"an":[55],"approximation":[56,107],"a":[58,130],"node-wise":[59],"separable":[60,112],"structure":[61],"thereby":[62],"removing":[63],"need":[65],"for":[66,82],"computations.":[70],"When":[71],"leveraged":[72],"Markov":[74],"random":[75],"field":[76],"and":[78,114],"message":[79],"passing":[80],"algorithms":[81],"inference,":[83],"likelihoods":[85,113],"facilitate":[86],"decentralised":[87],"estimation":[88,119],"networks":[91],"as":[92,94],"well":[93],"scalable":[95],"computation":[96],"schemes":[97],"centralised":[99],"settings.":[100],"establish":[102],"connection":[104],"between":[105],"quality":[108],"proposed":[111],"accuracy":[116],"based":[120],"individual":[122],"histories.":[124],"demonstrate":[126],"this":[127],"approach":[128],"network":[132],"self-localisation":[133],"example.":[134]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
