{"id":"https://openalex.org/W1923858626","doi":"https://doi.org/10.5075/epfl-thesis-4837","title":"Sensing and Recovery under Sparsity Constraints : Theory and Applications","display_name":"Sensing and Recovery under Sparsity Constraints : Theory and Applications","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W1923858626","doi":"https://doi.org/10.5075/epfl-thesis-4837","mag":"1923858626"},"language":"en","primary_location":{"id":"pmh:oai:infoscience.epfl.ch:150478","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/150478","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/150478","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085950460","display_name":"Ali Hormati","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hormati, Ali","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5085950460"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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":0.9983999729156494,"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":0.9983999729156494,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9775000214576721,"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/compressed-sensing","display_name":"Compressed sensing","score":0.7223225831985474},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7172463536262512},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7009875774383545},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.6744095087051392},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5617234110832214},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5347211956977844},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.48040202260017395},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.42674359679222107},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.41914287209510803},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.41290926933288574},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39484134316444397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3940417766571045},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2931690812110901}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7223225831985474},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7172463536262512},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7009875774383545},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.6744095087051392},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5617234110832214},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5347211956977844},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.48040202260017395},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.42674359679222107},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.41914287209510803},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.41290926933288574},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39484134316444397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3940417766571045},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2931690812110901},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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}],"mesh":[],"locations_count":4,"locations":[{"id":"pmh:oai:infoscience.epfl.ch:150478","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/150478","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:150478","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/52296","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":null,"raw_type":"doctoral thesis"},{"id":"doi:10.5075/epfl-thesis-4837","is_oa":true,"landing_page_url":"https://doi.org/10.5075/epfl-thesis-4837","pdf_url":null,"source":{"id":"https://openalex.org/S4306400488","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"thesis"},{"id":"mag:1923858626","is_oa":false,"landing_page_url":"https://infoscience.epfl.ch/record/150478","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:150478","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/150478","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":[{"score":0.6499999761581421,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1936178334","https://openalex.org/W2949327578","https://openalex.org/W2809866471","https://openalex.org/W191848727","https://openalex.org/W2687213666","https://openalex.org/W1978465754","https://openalex.org/W2280506658","https://openalex.org/W2158537680","https://openalex.org/W2149213383","https://openalex.org/W2089957712","https://openalex.org/W2479914246","https://openalex.org/W2661995953","https://openalex.org/W2588855895","https://openalex.org/W2952153281","https://openalex.org/W2766720529","https://openalex.org/W2099267803","https://openalex.org/W4279184","https://openalex.org/W2612617244","https://openalex.org/W2108911994","https://openalex.org/W2982320897"],"abstract_inverted_index":{"Popular":[0],"transforms,":[1],"like":[2],"the":[3,8,15,27,50,69,88,99,103,147,181,218,222,225,228,231,239,247,253,267,285,298,333,338,360,377,395,408,421,458,461,471,475,511,520,523,529,537,544,558,562,566,571],"discrete":[4],"cosine":[5],"transform":[6,41],"or":[7],"wavelet":[9],"transform,":[10],"owe":[11],"their":[12,372],"success":[13],"to":[14,80,98,108,136,145,166,191,227,238,364,429,444,478,485,516,536],"fact":[16],"that":[17,217],"they":[18,44],"promote":[19],"sparsity.":[20],"These":[21],"transforms":[22],"are":[23,317,362,392,398],"capable":[24],"of":[25,29,33,52,76,90,102,117,141,161,174,177,185,224,243,269,300,307,359,379,404,410,420,460,490,522,543,565],"extracting":[26],"structure":[28],"a":[30,39,46,84,171,402,418,437,488,495,499,526,541],"large":[31,438,496],"class":[32],"signals":[34,82,154,309,391],"and":[35,56,120,127,131,134,149,158,187,196,203,213,245,278,304,323,342,347,449,482,553,568],"representing":[36],"them":[37],"by":[38,319,401,507],"few":[40,500],"coefficients.":[42],"Therefore,":[43],"play":[45],"major":[47,66],"role":[48],"in":[49,83,230,252,432,494],"compression":[51],"speech,":[53],"audio,":[54],"image":[55],"video":[57],"signals.":[58,73,104],"Besides":[59],"data":[60],"compression,":[61],"sparsity":[62,369],"can":[63,560],"also":[64,343,464],"have":[65,465],"impact":[67],"on":[68,266,352,371,540],"way":[70],"we":[71,234,262,290,296,375,442,469,550],"acquire":[72,504],"The":[74,139,355,389,412],"idea":[75],"sparseness":[77],"leads":[78],"us":[79],"sample":[81],"compact":[85],"form,":[86],"i.e.,":[87,194],"number":[89,268],"samples":[91,506],"should":[92],"be":[93,313,430],"as":[94,96,114,417],"close":[95],"possible":[97],"information":[100,137],"rate":[101,116,176],"This":[105],"gave":[106],"rise":[107],"some":[109,433],"new":[110],"research":[111],"fields":[112],"such":[113],"finite":[115,175],"innovation":[118,178],"sampling":[119,179,202,334,340,481,552],"compressed":[121],"sensing,":[122,133],"with":[123,170,337,498,556],"applications":[124,366],"including":[125],"medical":[126],"seismic":[128],"imaging,":[129],"distributed":[130,302],"remote":[132],"analog":[135],"conversion.":[138],"goal":[140,476],"this":[142,192],"dissertation":[143],"is":[144,427,477,515,525,532],"advance":[146],"acquisition":[148],"reconstruction":[150,204,306,349,452],"techniques":[151,382,453],"for":[152,180,206,272,332,383],"sparse":[153,325,431],"from":[155],"both":[156],"theoretical":[157,211],"practical":[159],"points":[160],"view,":[162],"paying":[163],"special":[164,201,446],"attention":[165,237],"applications.":[167],"We":[168,199,328,503],"start":[169],"quick":[172],"review":[173],"continuous-time":[182],"periodic":[183,241],"stream":[184,242],"Diracs":[186,244],"provide":[188],"two":[189,208,308,330,357,365],"extensions":[190],"framework,":[193],"equal-weight":[195],"multiframe":[197],"scenarios.":[198],"design":[200,479],"algorithms":[205,220],"these":[207],"extensions.":[209],"Our":[210],"analysis":[212],"simulation":[214],"results":[215,226],"indicate":[216],"proposed":[219],"improve":[221,457],"robustness":[223,459],"uncertainties":[229],"measurements.":[232,502],"Then,":[233],"turn":[235],"our":[236],"discrete-time":[240],"investigate":[246,291],"corresponding":[248],"support":[249,273],"recovery":[250,274,483,554],"problem":[251,299,473],"noisy":[254],"setting.":[255],"By":[256],"adapting":[257],"an":[258,292,320,345],"estimation":[259],"theoretic":[260],"approach,":[261,549],"specifically":[263],"derive":[264],"conditions":[265],"measurements":[270,567],"required":[271],"using":[275,386],"lowpass":[276],"Fourier":[277],"i.i.d.":[279],"standard":[280],"Gaussian":[281],"measurement":[282,530],"matrices.":[283],"Following":[284],"classical":[286,545],"settings":[287],"mentioned":[288],"above,":[289],"interesting":[293],"scenario":[294],"where":[295,474],"study":[297,329,376],"non-adaptive":[301,546],"sensing":[303],"centralized":[305],"which":[310,367,397,426,454,557],"may":[311],"not":[312,455,533],"themselves":[314],"sparse,":[315,491],"but":[316,463],"linked":[318],"unknown":[321,422],"linear":[322],"time-invariant":[324],"filtering":[326],"operation.":[327],"strategies":[331],"process":[335,531],"along":[336],"achievable":[339],"pairs":[341],"propose":[344,443,551],"efficient":[346],"robust":[348],"algorithm":[350],"based":[351],"annihilating":[353],"filters.":[354],"last":[356],"chapters":[358],"thesis":[361],"devoted":[363],"involve":[368],"constraints":[370],"solutions.":[373],"First,":[374],"effectiveness":[378],"sparsity-based":[380,450],"regularization":[381],"breast":[384],"screening":[385],"ultrasound":[387,390,413],"tomography.":[388],"sent":[393],"through":[394],"object":[396],"then":[399],"received":[400],"set":[403,489],"receivers":[405],"placed":[406],"around":[407],"region":[409],"interest.":[411],"propagation":[414],"pattern":[415],"varies":[416],"function":[419],"sound":[423],"speed":[424],"distribution":[425],"assumed":[428],"appropriate":[434,480],"basis.":[435],"Being":[436],"scale":[439],"optimization":[440],"problem,":[441],"employ":[445],"forward":[447],"modeling":[448],"regularized":[451],"only":[456],"results,":[462],"reasonable":[466],"complexity.":[467],"Second,":[468],"consider":[470],"epidemiology":[472],"mechanisms":[484],"successfully":[486,569],"identify":[487,570],"virally-infected":[492],"people":[493],"population":[497,512],"collective":[501,505],"sending":[508],"agents":[509],"inside":[510],"whose":[513],"task":[514],"contact":[517],"people.":[518,573],"Since":[519],"transfer":[521],"disease":[524],"probabilistic":[527,563],"phenomenon,":[528],"fully":[534],"known":[535],"decoder.":[538],"Based":[539],"variation":[542],"group":[547],"testing":[548],"procedures":[555],"decoder":[559],"overcome":[561],"nature":[564],"infected":[572]},"counts_by_year":[{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2016-06-24T00:00:00"}
