{"id":"https://openalex.org/W1483764184","doi":"https://doi.org/10.5075/epfl-thesis-5378","title":"Compressive Sampling Strategies for Multichannel Signals : Theory and Applications","display_name":"Compressive Sampling Strategies for Multichannel Signals : Theory and Applications","publication_year":2012,"publication_date":"2012-01-01","ids":{"openalex":"https://openalex.org/W1483764184","doi":"https://doi.org/10.5075/epfl-thesis-5378","mag":"1483764184"},"language":"en","primary_location":{"id":"pmh:oai:infoscience.epfl.ch:180205","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/180205","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"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":"Text"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://infoscience.epfl.ch/record/180205","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056404513","display_name":"Mohammad Golbabaee","orcid":"https://orcid.org/0000-0001-5822-2990"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Golbabaee, Mohammad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5056404513"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3078,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5780046,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9993000030517578,"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":0.9993000030517578,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9779999852180481,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9333000183105469,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/notice","display_name":"Notice","score":0.49331584572792053},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.49177077412605286},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.47685348987579346},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4558209180831909},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.448616623878479},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.41827383637428284},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.41344940662384033},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4054708182811737},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3665073812007904},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.22356903553009033},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15270817279815674}],"concepts":[{"id":"https://openalex.org/C2779913896","wikidata":"https://www.wikidata.org/wiki/Q7063001","display_name":"Notice","level":2,"score":0.49331584572792053},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.49177077412605286},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.47685348987579346},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4558209180831909},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.448616623878479},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.41827383637428284},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.41344940662384033},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4054708182811737},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3665073812007904},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.22356903553009033},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15270817279815674},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"pmh:oai:infoscience.epfl.ch:180205","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/180205","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"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":"Text"},{"id":"pmh:oai:infoscience.tind.io:180205","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/record/180205/files/EPFL_TH5378.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"doctoral thesis"},{"id":"doi:10.5075/epfl-thesis-5378","is_oa":true,"landing_page_url":"https://doi.org/10.5075/epfl-thesis-5378","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dissertation"},{"id":"mag:1483764184","is_oa":false,"landing_page_url":"https://infoscience.epfl.ch/record/180205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:infoscience.epfl.ch:180205","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/180205","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"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":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2913033225","https://openalex.org/W2952521922","https://openalex.org/W2136504031","https://openalex.org/W2651140493","https://openalex.org/W3201143781"],"abstract_inverted_index":{"Over":[0],"the":[1,21,59,75,80,87,98,104,114,123,135,239,244,253,282,313,330,339,344,349,353,356,374,430,437,462,485,505,508,539],"past":[2],"decade":[3],"researches":[4],"in":[5,53,79,109,131,148,336,443,458,480,538],"applied":[6],"mathematics,":[7],"signal":[8,38,85,171,410,447],"processing":[9,39],"and":[10,96,122,126,144,181,206,321,352,369,372,400,436,464,489,529,545],"communications":[11],"have":[12,50,403],"introduced":[13],"compressive":[14,300,365,420],"sampling":[15,23,222,350,421],"(CS)":[16],"as":[17,287],"an":[18,413],"alternative":[19],"to":[20,34,43,66,74,150,252,311,364,379,397,515,525],"Shannon":[22],"theorem.":[24],"The":[25,156,477],"two":[26,165,362],"key":[27],"observations":[28],"making":[29],"CS":[30,71,106,195,229,247,295,342],"theory":[31,107],"widely":[32],"applicable":[33],"numerous":[35,408],"areas":[36],"of":[37,61,89,117,119,129,137,159,241,246,256,258,315,333,338,341,347,355,376,391,432,439,466,475,507,542],"are:":[40],"i)":[41],"due":[42],"their":[44,469],"structural":[45],"properties,":[46],"natural":[47],"signals":[48,121],"typically":[49],"sparse":[51],"representations":[52],"properly":[54],"chosen":[55,81],"orthogonal":[56],"bases,":[57],"ii)":[58],"number":[60,245,340,431],"linear":[62,275],"non-adaptive":[63],"measurements":[64,248],"required":[65],"acquire":[67],"high-dimensional":[68],"data":[69,88,130,146,228,271,294],"with":[70,451],"is":[72,92,162,484,535],"proportional":[73,251],"signal\u2019s":[76],"sparsity":[77,100,345,506],"level":[78,346],"basis.":[82],"In":[83],"multichannel":[84,120,170,186,227,270,293,409,446],"applications":[86,118,133,390,418],"different":[90,445],"channels":[91],"often":[93],"highly":[94],"correlated":[95],"therefore":[97],"unstructured":[99],"hypothesis":[101],"deployed":[102],"by":[103,273,473,496,503],"classical":[105,540],"results":[108,424,513],"suboptimal":[110],"measurement":[111],"rates.":[112],"Meanwhile,":[113],"wide":[115],"range":[116],"extremely":[124],"large":[125],"increasing":[127],"flow":[128],"those":[132],"motivates":[134],"development":[136],"more":[138,152],"comprehensive":[139],"models":[140,167],"incorporating":[141],"both":[142],"inter":[143],"intra-channel":[145],"structures":[147],"order":[149],"achieve":[151,219,511],"efficient":[153,169,323,531],"dimensionality":[154],"reduction.":[155],"main":[157,478],"focus":[158],"this":[160,216,242,334,494],"thesis":[161],"on":[163,199,407],"studying":[164],"new":[166],"for":[168,185,204,224,269,318,382,415],"compressed":[172],"sensing.":[173],"Our":[174,210,262,326],"first":[175],"approach":[176,217,264,335],"proposes":[177],"a":[178,189,193,225,266,274,291,299,307,319,404,426,444,452,497,527],"simultaneous":[179],"low-rank":[180,205],"joint-sparse":[182,207],"matrix":[183,208],"model":[184,268,493],"signals.":[187],"As":[188,290,412],"result,":[190,292],"we":[191,279,305,449,510],"introduce":[192],"novel":[194,308],"recovery":[196,296,368],"scheme":[197,310],"based":[198],"Nuclear-l2/l1":[200],"norm":[201],"convex":[202],"minimization":[203],"approximation.":[209],"theoretical":[211,327],"analysis":[212,237],"indicates":[213],"that":[214,281,389,534],"using":[215,520],"can":[218,402],"significantly":[220],"lower":[221],"rates":[223],"robust":[226,320],"acquisition":[230],"than":[231],"state-of-the-art":[232,380,516],"methods.":[233,517],"More":[234,518],"remarkably,":[235,519],"our":[236,377,423],"confirms":[238],"near-optimality":[240],"approach:":[243],"are":[249,285,394],"nearly":[250],"few":[254],"degrees":[255],"freedom":[257],"such":[259],"structured":[260],"data.":[261],"second":[263],"introduces":[265],"stronger":[267],"synthesized":[272],"mixture":[276,283,316,357],"model.":[277],"Here":[278],"assume":[280],"parameters":[284,317],"given":[286,468],"side":[288],"information.":[289],"turns":[297],"into":[298],"source":[301,324,370],"separation":[302],"problem,":[303],"where":[304],"propose":[306,526],"decorrelating":[309],"exploit":[312],"knowledge":[314],"numerically":[322],"identification.":[325],"guarantees":[328],"explain":[329],"fundamental":[331],"limits":[332],"terms":[337],"measurements,":[343],"sources,":[348],"noise,":[351],"conditioning":[354],"parameters.":[358],"We":[359,492],"apply":[360],"these":[361,392],"approaches":[363,381],"hyperspectral":[366,386,398],"image":[367],"separation,":[371],"compare":[373],"efficiency":[375],"methods":[378,393],"several":[383],"challenging":[384],"real-world":[385],"datasets.":[387],"Note":[388],"not":[395],"limited":[396],"imagery":[399],"it":[401],"broad":[405],"impact":[406],"applications.":[411],"example,":[414],"sensor":[416],"network":[417],"deploying":[419],"schemes,":[422],"indicate":[425],"tight":[427],"tradeoff":[428,486],"between":[429,487],"available":[433],"sensors":[434],"(channels)":[435],"complexity/cost":[438],"each":[440],"sensor.":[441],"Finally,":[442],"application,":[448],"deal":[450],"simple":[453],"but":[454],"very":[455],"important":[456],"problem":[457,495,501],"computer":[459],"vision":[460],"namely":[461],"detection":[463],"localization":[465],"people":[467],"multi-view":[470],"silhouettes":[471],"captured":[472],"networks":[474],"cameras.":[476],"challenge":[479],"many":[481],"existing":[482],"solutions":[483],"robustness":[488],"numerical":[490],"efficiency.":[491],"boolean":[498,521],"(non-linear)":[499],"inverse":[500],"where,":[502],"penalizing":[504],"solution,":[509],"accurate":[512],"comparable":[514],"arithmetics":[522],"enables":[523],"us":[524],"real-time":[528],"memory":[530],"approximation":[532],"algorithm":[533],"mainly":[536],"rooted":[537],"literature":[541],"group":[543],"testing":[544],"set":[546],"cover.":[547]},"counts_by_year":[{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-23T05:56:39.545243","created_date":"2016-06-24T00:00:00"}
