{"id":"https://openalex.org/W1633433680","doi":"https://doi.org/10.1109/tsp.2015.2463252","title":"Performance Limits of Segmented Compressive Sampling: Correlated Measurements Versus Bits","display_name":"Performance Limits of Segmented Compressive Sampling: Correlated Measurements Versus Bits","publication_year":2015,"publication_date":"2015-07-31","ids":{"openalex":"https://openalex.org/W1633433680","doi":"https://doi.org/10.1109/tsp.2015.2463252","mag":"1633433680"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2015.2463252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2015.2463252","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1411.5178","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103667001","display_name":"Hao Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Fang","raw_affiliation_strings":["Department of Electrical Engineering, University of Washington, Seattle, WA, USA","Department of Electrical Engineering University of Washington, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]},{"raw_affiliation_string":"Department of Electrical Engineering University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055234860","display_name":"Sergiy A. Vorobyov","orcid":"https://orcid.org/0000-0001-7249-647X"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Sergiy A. Vorobyov","raw_affiliation_strings":["Department of Signal Processing and Acoustics, Aalto University, Aalto, Finland","[Dept. of Signal Processing and Acoustics, Aalto University, Aalto, Finland]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Processing and Acoustics, Aalto University, Aalto, Finland","institution_ids":["https://openalex.org/I9927081"]},{"raw_affiliation_string":"[Dept. of Signal Processing and Acoustics, Aalto University, Aalto, Finland]","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022850202","display_name":"Hai Jiang","orcid":"https://orcid.org/0000-0003-1042-4897"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hai Jiang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada","Department of Electrical and Computer Engineering , University of Alberta , Edmonton , Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada","institution_ids":["https://openalex.org/I154425047"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering , University of Alberta , Edmonton , Canada","institution_ids":["https://openalex.org/I154425047"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5796,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66149646,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"63","issue":"22","first_page":"6061","last_page":"6073"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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":0.9970999956130981,"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/compressed-sensing","display_name":"Compressed sensing","score":0.8051966428756714},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6998202800750732},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6634964942932129},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.644779622554779},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5674977898597717},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5276507139205933},{"id":"https://openalex.org/keywords/oversampling","display_name":"Oversampling","score":0.4946388900279999},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.48588699102401733},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.4813119173049927},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4348275661468506},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3367980420589447},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.2763168215751648},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2501002550125122},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20686587691307068},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.19701337814331055},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11556050181388855},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.08952343463897705},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.0830119252204895},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.07840967178344727}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.8051966428756714},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6998202800750732},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6634964942932129},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.644779622554779},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5674977898597717},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5276507139205933},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.4946388900279999},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.48588699102401733},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.4813119173049927},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4348275661468506},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3367980420589447},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2763168215751648},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2501002550125122},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20686587691307068},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.19701337814331055},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11556050181388855},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.08952343463897705},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0830119252204895},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.07840967178344727},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2015.2463252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2015.2463252","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"},{"id":"pmh:oai:arXiv.org:1411.5178","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1411.5178","pdf_url":"https://arxiv.org/pdf/1411.5178","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1411.5178","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1411.5178","pdf_url":"https://arxiv.org/pdf/1411.5178","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W189254822","https://openalex.org/W1494099594","https://openalex.org/W1608472120","https://openalex.org/W1986931325","https://openalex.org/W1990992471","https://openalex.org/W2030449718","https://openalex.org/W2091482891","https://openalex.org/W2099111195","https://openalex.org/W2103164394","https://openalex.org/W2103955025","https://openalex.org/W2104357403","https://openalex.org/W2109379066","https://openalex.org/W2119667497","https://openalex.org/W2120189607","https://openalex.org/W2127300249","https://openalex.org/W2129131372","https://openalex.org/W2130199634","https://openalex.org/W2141556672","https://openalex.org/W2143236825","https://openalex.org/W2152824512","https://openalex.org/W2154304330","https://openalex.org/W2161950100","https://openalex.org/W2210387432","https://openalex.org/W2296616510","https://openalex.org/W2539488803","https://openalex.org/W2595142274","https://openalex.org/W3101990100","https://openalex.org/W3158755844","https://openalex.org/W4250955649","https://openalex.org/W4297825594","https://openalex.org/W4300840296"],"related_works":["https://openalex.org/W2378166785","https://openalex.org/W2152863486","https://openalex.org/W2156466545","https://openalex.org/W2379468505","https://openalex.org/W3104324607","https://openalex.org/W4206981968","https://openalex.org/W1987102304","https://openalex.org/W2601968125","https://openalex.org/W2308961925","https://openalex.org/W4285251805"],"abstract_inverted_index":{"This":[0],"paper":[1],"discusses":[2],"performance":[3,60],"limits":[4],"of":[5,22],"the":[6,20,27,38,42,52,59,64,71,77,94,97,107,113,119,122,138],"segmented":[7,28,72,108,139],"compressive":[8],"sampling":[9],"(CS)":[10],"system":[11],"that":[12,19,58,96,121],"collects":[13],"correlated":[14,124],"measurements.":[15],"It":[16,56],"is":[17,49,85,133],"shown":[18],"effect":[21],"correlation":[23,66],"among":[24,67],"measurements":[25,68,104,125],"for":[26,87,137],"CS":[29,73,79,109,115],"can":[30],"be":[31],"characterized":[32],"by":[33,70,106],"a":[34,88,131,134],"penalty":[35,47],"term":[36,48],"in":[37],"corresponding":[39],"bounds":[40],"on":[41],"measurement":[43,83],"rate.":[44],"Moreover,":[45],"this":[46],"vanishing":[50],"as":[51],"signal":[53,98,132],"dimension":[54],"increases.":[55],"means":[57],"degradation":[61],"due":[62],"to":[63,76,112],"fixed":[65],"obtained":[69,105],"(as":[74,110],"compared":[75,111],"standard":[78,114],"with":[80,93,102],"equivalent":[81],"size":[82],"matrix)":[84],"negligible":[86],"high-dimensional":[89],"signal.":[90],"In":[91],"combination":[92],"fact":[95,120],"reconstruction":[99],"quality":[100],"improves":[101],"additional":[103,117,123],"without":[116],"measurements),":[118],"also":[126],"provide":[127],"new":[128],"information":[129],"about":[130],"strong":[135],"argument":[136],"CS.":[140]},"counts_by_year":[{"year":2015,"cited_by_count":2}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2016-06-24T00:00:00"}