{"id":"https://openalex.org/W2407417563","doi":"https://doi.org/10.1109/icassp.2016.7472559","title":"Independent versus repeated measurements: A performance quantification via state evolution","display_name":"Independent versus repeated measurements: A performance quantification via state evolution","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2407417563","doi":"https://doi.org/10.1109/icassp.2016.7472559","mag":"2407417563"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7472559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472559","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101838388","display_name":"Yang Lu","orcid":"https://orcid.org/0000-0001-8322-5130"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Yang Lu","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Imperial College London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Imperial College London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100752236","display_name":"Wei Dai","orcid":"https://orcid.org/0000-0002-4781-3485"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wei Dai","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Imperial College London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Imperial College London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101838388"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":1.1581,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.80618382,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"4653","last_page":"4657"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9993000030517578,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44923973083496094},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44707223773002625}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44923973083496094},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44707223773002625}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7472559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472559","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1655664036","https://openalex.org/W1676074242","https://openalex.org/W1983481547","https://openalex.org/W2007527271","https://openalex.org/W2013694832","https://openalex.org/W2020282020","https://openalex.org/W2075172746","https://openalex.org/W2082029531","https://openalex.org/W2090861849","https://openalex.org/W2098521117","https://openalex.org/W2106407813","https://openalex.org/W2112387511","https://openalex.org/W2115144080","https://openalex.org/W2127995963","https://openalex.org/W2130299261","https://openalex.org/W2136979582","https://openalex.org/W2610971674","https://openalex.org/W2963702538","https://openalex.org/W3098848552","https://openalex.org/W6637044157"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"The":[0,50,128,141],"paper":[1],"quantifies":[2],"and":[3,14,102,131],"compares":[4],"the":[5,80,83,90,97,105,109,112,119,135,138,147],"exact":[6],"asymptotic":[7,98,106],"performance":[8,84,99,139],"of":[9,82,100,111,121,137],"multiple":[10,22],"measurement":[11,23,57,66,113,122],"vector":[12],"(MMV)":[13],"distributed":[15],"sensing":[16],"(DS)":[17],"models.":[18],"Both":[19],"models":[20],"assume":[21],"instances":[24,123],"y":[25],"<sub":[26,31,35,40],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[27,32,36,41],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">k</sub>":[28,33,37,42],"=":[29,45],"A":[30],"x":[34],"+":[38],"w":[39],",":[43],"k":[44],"1,":[46],"2,":[47],"...,":[48],"K.":[49],"difference":[51,85],"is":[52,86,94,144],"that":[53,72,108],"MMV":[54,77,101],"involves":[55],"identical":[56],"matrices":[58,63,114],"whereas":[59],"DS":[60,73,103],"allows":[61],"different":[62,65],"for":[64,150],"instances.":[67],"It":[68],"has":[69],"been":[70],"recognized":[71],"works":[74],"better":[75],"than":[76],"empirically.":[78],"However,":[79],"quantification":[81],"not":[87],"available":[88],"in":[89,104],"literature.":[91],"Our":[92],"contribution":[93],"to":[95],"quantify":[96],"regime":[107],"dimensions":[110],"approach":[115],"infinity":[116],"proportionally":[117],"but":[118],"number":[120],"K":[124],"remains":[125],"a":[126],"constant.":[127],"case":[129],"study":[130],"numerical":[132],"results":[133],"justify":[134],"accuracy":[136],"quantification.":[140],"analysis":[142],"technique":[143],"based":[145],"on":[146],"state":[148],"evolution":[149],"approximate":[151],"message":[152],"passing.":[153]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"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"}