{"id":"https://openalex.org/W2094501628","doi":"https://doi.org/10.1109/isit.2012.6283951","title":"Subsampling at information theoretically optimal rates","display_name":"Subsampling at information theoretically optimal rates","publication_year":2012,"publication_date":"2012-07-01","ids":{"openalex":"https://openalex.org/W2094501628","doi":"https://doi.org/10.1109/isit.2012.6283951","mag":"2094501628"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2012.6283951","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2012.6283951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Symposium on Information Theory Proceedings","raw_type":"proceedings-article"},"type":"conference-paper","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/A5010342958","display_name":"Adel Javanmard","orcid":"https://orcid.org/0000-0003-1934-8747"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adel Javanmard","raw_affiliation_strings":["Department of Electrical Engineering, University of Stanford, USA","Dept of Electrical Engineering, Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Dept of Electrical Engineering, Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011999109","display_name":"Andrea Montanari","orcid":"https://orcid.org/0000-0002-0267-8574"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrea Montanari","raw_affiliation_strings":["Department of Electrical Engineering and Department of Statistics, University of Stanford, USA","Department of Electrical Engineering and Department of Statistics, Stanford University,#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Department of Statistics, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Department of Electrical Engineering and Department of Statistics, Stanford University,#TAB#","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2431","last_page":"2435"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9993000030517578,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9990000128746033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5908059477806091},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.5769200325012207},{"id":"https://openalex.org/keywords/nyquist-rate","display_name":"Nyquist rate","score":0.5664539933204651},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5523616671562195},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.5507270097732544},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5465717315673828},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.541946530342102},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5374287962913513},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.5052791237831116},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.49619823694229126},{"id":"https://openalex.org/keywords/discrete-time-signal","display_name":"Discrete-time signal","score":0.49330249428749084},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4522862136363983},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.424185574054718},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4182668626308441},{"id":"https://openalex.org/keywords/signal-transfer-function","display_name":"Signal transfer function","score":0.37960702180862427},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2651096284389496},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.17544838786125183},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14881759881973267},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.13583165407180786},{"id":"https://openalex.org/keywords/analog-signal","display_name":"Analog signal","score":0.12423375248908997}],"concepts":[{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5908059477806091},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.5769200325012207},{"id":"https://openalex.org/C65914096","wikidata":"https://www.wikidata.org/wiki/Q6273772","display_name":"Nyquist rate","level":4,"score":0.5664539933204651},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5523616671562195},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.5507270097732544},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5465717315673828},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.541946530342102},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5374287962913513},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.5052791237831116},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.49619823694229126},{"id":"https://openalex.org/C146749787","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete-time signal","level":5,"score":0.49330249428749084},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4522862136363983},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.424185574054718},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4182668626308441},{"id":"https://openalex.org/C131021393","wikidata":"https://www.wikidata.org/wiki/Q7512759","display_name":"Signal transfer function","level":4,"score":0.37960702180862427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2651096284389496},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.17544838786125183},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14881759881973267},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.13583165407180786},{"id":"https://openalex.org/C13412647","wikidata":"https://www.wikidata.org/wiki/Q174948","display_name":"Analog signal","level":3,"score":0.12423375248908997},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit.2012.6283951","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2012.6283951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Symposium on Information Theory Proceedings","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":26,"referenced_works":["https://openalex.org/W639989723","https://openalex.org/W1536930200","https://openalex.org/W1986051087","https://openalex.org/W1991215696","https://openalex.org/W1991528082","https://openalex.org/W2076905373","https://openalex.org/W2082029531","https://openalex.org/W2118473837","https://openalex.org/W2123622978","https://openalex.org/W2135479785","https://openalex.org/W2139012746","https://openalex.org/W2145096794","https://openalex.org/W2172679141","https://openalex.org/W2173526877","https://openalex.org/W2418937273","https://openalex.org/W2571527823","https://openalex.org/W2610971674","https://openalex.org/W2798333393","https://openalex.org/W2949789221","https://openalex.org/W3098848552","https://openalex.org/W3100706365","https://openalex.org/W3102627364","https://openalex.org/W3125530803","https://openalex.org/W4211251910","https://openalex.org/W4298371340","https://openalex.org/W6714914520"],"related_works":["https://openalex.org/W2356275480","https://openalex.org/W2899148860","https://openalex.org/W2379468505","https://openalex.org/W2793783688","https://openalex.org/W2468414543","https://openalex.org/W2159420092","https://openalex.org/W2294732742","https://openalex.org/W2295430099","https://openalex.org/W2147292092","https://openalex.org/W2115504648"],"abstract_inverted_index":{"We":[0,137],"study":[1],"the":[2,23,31,39,44,59,67,76,80,84,98,106,149,153,157,161],"problem":[3],"of":[4,58,83,108,134,156],"sampling":[5,40,77,102,150],"a":[6,18,52,94,101,130],"random":[7,62,122,132],"signal":[8,24,32,60,68],"with":[9],"sparse":[10],"support":[11,82,155],"in":[12,111],"frequency":[13,81,154],"domain.":[14],"Shannon":[15],"famously":[16],"considered":[17],"scheme":[19,53,103,142],"that":[20,30,54,66,140],"instantaneously":[21],"samples":[22,57,120],"at":[25,61,121],"equispaced":[26],"times.":[27,63,123],"He":[28],"proved":[29,65],"can":[33,69],"be":[34,70],"reconstructed":[35],"as":[36,38,146,148],"long":[37],"rate":[41,78,151],"exceeds":[42,79,152],"twice":[43],"bandwidth":[45],"(Nyquist":[46],"rate).":[47],"Cand\u00e8s,":[48],"Romberg,":[49],"Tao":[50],"introduced":[51],"acquires":[55],"instantaneous":[56],"They":[64],"uniquely":[71],"and":[72,100],"efficiently":[73],"reconstructed,":[74],"provided":[75],"signal,":[85,99,158],"times":[86],"logarithmic":[87],"factors.":[88],"In":[89],"this":[90,125,141],"paper":[91],"we":[92,115],"consider":[93],"probabilistic":[95],"model":[96],"for":[97],"inspired":[104],"by":[105,128],"idea":[107],"spatial":[109],"coupling":[110],"coding":[112],"theory.":[113],"Namely,":[114],"propose":[116],"to":[117],"acquire":[118],"non-instantaneous":[119],"Mathematically,":[124],"is":[126],"implemented":[127],"acquiring":[129],"small":[131],"subset":[133],"Gabor":[135],"coefficients.":[136],"show":[138],"empirically":[139],"achieves":[143],"correct":[144],"reconstruction":[145],"soon":[147],"thus":[159],"reaching":[160],"information":[162],"theoretic":[163],"limit.":[164]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}