{"id":"https://openalex.org/W4390044799","doi":"https://doi.org/10.1109/sdf-mfi59545.2023.10361452","title":"An O(log<sub>2</sub> N) SMC<sup>2</sup> Algorithm on Distributed Memory with an Approx. Optimal L-Kernel","display_name":"An O(log<sub>2</sub> N) SMC<sup>2</sup> Algorithm on Distributed Memory with an Approx. Optimal L-Kernel","publication_year":2023,"publication_date":"2023-11-27","ids":{"openalex":"https://openalex.org/W4390044799","doi":"https://doi.org/10.1109/sdf-mfi59545.2023.10361452"},"language":"en","primary_location":{"id":"doi:10.1109/sdf-mfi59545.2023.10361452","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sdf-mfi59545.2023.10361452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Symposium Sensor Data Fusion and International Conference on Multisensor Fusion and Integration (SDF-MFI)","raw_type":"proceedings-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/A5003665024","display_name":"Conor Rosato","orcid":"https://orcid.org/0000-0001-8394-7344"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Conor Rosato","raw_affiliation_strings":["University of Liverpool,Department of Pharmacology and Therapeutics,United Kingdom","Department of Pharmacology and Therapeutics, University of Liverpool, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Liverpool,Department of Pharmacology and Therapeutics,United Kingdom","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"Department of Pharmacology and Therapeutics, University of Liverpool, United Kingdom","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019054446","display_name":"Alessandro Varsi","orcid":"https://orcid.org/0000-0003-2218-4720"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Alessandro Varsi","raw_affiliation_strings":["University of Liverpool,Department of Electrical Engineering and Electronics,United Kingdom","Department of Electrical Engineering and Electronics, University of Liverpool, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Liverpool,Department of Electrical Engineering and Electronics,United Kingdom","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"Department of Electrical Engineering and Electronics, University of Liverpool, United Kingdom","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007595974","display_name":"Joshua Murphy","orcid":"https://orcid.org/0000-0001-9085-5755"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Joshua Murphy","raw_affiliation_strings":["University of Liverpool,Department of Electrical Engineering and Electronics,United Kingdom","Department of Electrical Engineering and Electronics, University of Liverpool, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Liverpool,Department of Electrical Engineering and Electronics,United Kingdom","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"Department of Electrical Engineering and Electronics, University of Liverpool, United Kingdom","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083636287","display_name":"Simon Maskell","orcid":"https://orcid.org/0000-0003-1917-2913"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Simon Maskell","raw_affiliation_strings":["University of Liverpool,Department of Electrical Engineering and Electronics,United Kingdom","Department of Electrical Engineering and Electronics, University of Liverpool, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Liverpool,Department of Electrical Engineering and Electronics,United Kingdom","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"Department of Electrical Engineering and Electronics, University of Liverpool, United Kingdom","institution_ids":["https://openalex.org/I146655781"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7948,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.88352371,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9916999936103821,"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":0.9916999936103821,"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9861999750137329,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9797999858856201,"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/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.7393882274627686},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6180411577224731},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.5405951142311096},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.49727728962898254},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4734216332435608},{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.4621070325374603},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4611850380897522},{"id":"https://openalex.org/keywords/auxiliary-particle-filter","display_name":"Auxiliary particle filter","score":0.4179891347885132},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3929252028465271},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3399979770183563},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.2737288773059845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2654276490211487},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18662375211715698}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7393882274627686},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6180411577224731},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.5405951142311096},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.49727728962898254},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4734216332435608},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.4621070325374603},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4611850380897522},{"id":"https://openalex.org/C52483021","wikidata":"https://www.wikidata.org/wiki/Q4827310","display_name":"Auxiliary particle filter","level":5,"score":0.4179891347885132},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3929252028465271},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3399979770183563},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.2737288773059845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2654276490211487},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18662375211715698},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.0},{"id":"https://openalex.org/C79334102","wikidata":"https://www.wikidata.org/wiki/Q3072268","display_name":"Ensemble Kalman filter","level":4,"score":0.0},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sdf-mfi59545.2023.10361452","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sdf-mfi59545.2023.10361452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Symposium Sensor Data Fusion and International Conference on Multisensor Fusion and Integration (SDF-MFI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4850962026","display_name":null,"funder_award_id":"EP/R018537/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320311904","display_name":"Wellcome Trust","ror":"https://ror.org/029chgv08"},{"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":38,"referenced_works":["https://openalex.org/W43927996","https://openalex.org/W1483307070","https://openalex.org/W1501586228","https://openalex.org/W1876120984","https://openalex.org/W1932940155","https://openalex.org/W2001032894","https://openalex.org/W2050555786","https://openalex.org/W2054747216","https://openalex.org/W2058849341","https://openalex.org/W2114456110","https://openalex.org/W2117443107","https://openalex.org/W2138309709","https://openalex.org/W2141585124","https://openalex.org/W2147357149","https://openalex.org/W2148301044","https://openalex.org/W2160337655","https://openalex.org/W2173482895","https://openalex.org/W2217402295","https://openalex.org/W2271646078","https://openalex.org/W2577537660","https://openalex.org/W2802252679","https://openalex.org/W2945648889","https://openalex.org/W2954040150","https://openalex.org/W2963977107","https://openalex.org/W3019156444","https://openalex.org/W3046573566","https://openalex.org/W3046922824","https://openalex.org/W3106379780","https://openalex.org/W3164436820","https://openalex.org/W3192708935","https://openalex.org/W3211330167","https://openalex.org/W3215540479","https://openalex.org/W4320908009","https://openalex.org/W4383218616","https://openalex.org/W4390445385","https://openalex.org/W6679529799","https://openalex.org/W6762496237","https://openalex.org/W6799698183"],"related_works":["https://openalex.org/W3144709167","https://openalex.org/W2368144031","https://openalex.org/W2162253570","https://openalex.org/W2355962871","https://openalex.org/W1824810860","https://openalex.org/W2758742130","https://openalex.org/W2126226614","https://openalex.org/W2406829934","https://openalex.org/W1497303808","https://openalex.org/W2075503097"],"abstract_inverted_index":{"Calibrating":[0],"statistical":[1],"models":[2],"using":[3,71],"Bayesian":[4],"inference":[5],"often":[6],"requires":[7],"both":[8],"accurate":[9,207],"and":[10,23,114,169,208],"timely":[11],"estimates":[12],"of":[13,15,41,109,151,165,177],"parameters":[14],"interest.":[16],"Particle":[17],"Markov":[18,59],"Chain":[19],"Monte":[20,25],"Carlo":[21,26],"(p-MCMC)":[22],"Sequential":[24],"Squared":[27],"(SMC":[28],"<sup":[29,82,121,138,190],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[30,83,122,139,191],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[31,84,123,140,192],")":[32],"are":[33,93],"two":[34],"methods":[35],"that":[36,92,142,188],"use":[37],"an":[38,124,136,147,160,170],"unbiased":[39],"estimate":[40],"the":[42,52,107,144,181,223],"log-likelihood":[43],"obtained":[44],"from":[45],"a":[46,57,175,184,196],"particle":[47],"filter":[48],"(PF)":[49],"to":[50,80,103,195,222],"evaluate":[51],"target":[53],"distribution.":[54],"P-MCMC":[55],"constructs":[56],"single":[58],"chain":[60],"which":[61,85,219],"is":[62,77,204,217],"sequential":[63,201],"by":[64],"nature":[65],"so":[66],"cannot":[67],"be":[68],"readily":[69],"parallelized":[70],"Distributed":[72],"Memory":[73],"(DM)":[74],"architectures.":[75],"This":[76],"in":[78],"contrast":[79],"SMC":[81,120,137,189],"includes":[86,143],"processes,":[87],"such":[88],"as":[89,95],"importance":[90],"sampling,":[91],"described":[94],"embarrassingly":[96],"parallel.":[97],"However,":[98],"difficulties":[99],"arise":[100],"when":[101,127],"attempting":[102],"parallelize":[104],"resampling.":[105],"None-the-less,":[106],"choice":[108],"backward":[110,167],"kernel,":[111,168],"recycling":[112,172],"scheme":[113],"compatibility":[115],"with":[116,129],"DM":[117,158,179],"architectures":[118],"makes":[119],"attractive":[125],"option":[126],"compared":[128],"p-MCMC.":[130,213],"In":[131],"this":[132],"paper,":[133],"we":[134],"present":[135],"framework":[141],"following":[145],"features:":[146],"optimal":[148,162],"(in":[149,163],"terms":[150,164],"time":[152],"complexity)":[153],"$\\mathcal{O}(\\log_2":[154],"N)$":[155],"parallelization":[156],"for":[157],"architectures,":[159],"approximately":[161],"accuracy)":[166],"efficient":[171],"scheme.":[173],"On":[174],"cluster":[176],"128":[178],"processors,":[180],"results":[182],"on":[183],"biomedical":[185],"application":[186],"show":[187],"achieves":[193],"up":[194],"70\u00d7":[197],"speed-up":[198],"vs":[199],"its":[200],"implementation.":[202],"It":[203],"also":[205],"more":[206],"roughly":[209],"54\u00d7":[210],"faster":[211],"than":[212],"A":[214],"GitHub":[215],"link":[216],"given":[218],"provides":[220],"access":[221],"code.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
