{"id":"https://openalex.org/W2615945947","doi":"https://doi.org/10.1109/tit.2017.2704111","title":"An Information-Theoretic Study for Joint Sparsity Pattern Recovery With Different Sensing Matrices","display_name":"An Information-Theoretic Study for Joint Sparsity Pattern Recovery With Different Sensing Matrices","publication_year":2017,"publication_date":"2017-05-15","ids":{"openalex":"https://openalex.org/W2615945947","doi":"https://doi.org/10.1109/tit.2017.2704111","mag":"2615945947"},"language":"en","primary_location":{"id":"doi:10.1109/tit.2017.2704111","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2017.2704111","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"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 Information Theory","raw_type":"journal-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/A5100690662","display_name":"Sangjun Park","orcid":"https://orcid.org/0000-0003-4975-042X"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Sangjun Park","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054154402","display_name":"Nam Yul Yu","orcid":"https://orcid.org/0000-0001-9265-712X"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Nam Yul Yu","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034347136","display_name":"Heung-No Lee","orcid":"https://orcid.org/0000-0001-8528-5778"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Heung-No Lee","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100690662"],"corresponding_institution_ids":["https://openalex.org/I39534123"],"apc_list":null,"apc_paid":null,"fwci":3.1213,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.91257693,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"63","issue":"9","first_page":"5559","last_page":"5571"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9987999796867371,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9980000257492065,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.8482366800308228},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.6364616751670837},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6271902322769165},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.6241015791893005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6144039630889893},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5746232271194458},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5626059770584106},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5275399684906006},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.5258974432945251},{"id":"https://openalex.org/keywords/sublinear-function","display_name":"Sublinear function","score":0.49174192547798157},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.4711436331272125},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.43139681220054626},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3290737271308899},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.3025915026664734},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2912755012512207},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24936866760253906},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.21155819296836853},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07265296578407288}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.8482366800308228},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.6364616751670837},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6271902322769165},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.6241015791893005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6144039630889893},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5746232271194458},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5626059770584106},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5275399684906006},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5258974432945251},{"id":"https://openalex.org/C117160843","wikidata":"https://www.wikidata.org/wiki/Q338652","display_name":"Sublinear function","level":2,"score":0.49174192547798157},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.4711436331272125},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.43139681220054626},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3290737271308899},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3025915026664734},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2912755012512207},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24936866760253906},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.21155819296836853},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07265296578407288},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"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},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tit.2017.2704111","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2017.2704111","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"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 Information Theory","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G3614130630","display_name":null,"funder_award_id":"NRF2015R1A2A1A05001826","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W340244495","https://openalex.org/W649866511","https://openalex.org/W1536252645","https://openalex.org/W1560153690","https://openalex.org/W1578953027","https://openalex.org/W1591116419","https://openalex.org/W1674742109","https://openalex.org/W1774526428","https://openalex.org/W1848264314","https://openalex.org/W1989476724","https://openalex.org/W1995875735","https://openalex.org/W2010221098","https://openalex.org/W2034118716","https://openalex.org/W2040869155","https://openalex.org/W2061761249","https://openalex.org/W2062002220","https://openalex.org/W2099904738","https://openalex.org/W2103583477","https://openalex.org/W2104357403","https://openalex.org/W2106407813","https://openalex.org/W2106460483","https://openalex.org/W2109379066","https://openalex.org/W2119667497","https://openalex.org/W2126644064","https://openalex.org/W2129131372","https://openalex.org/W2129638195","https://openalex.org/W2141556672","https://openalex.org/W2145096794","https://openalex.org/W2156587627","https://openalex.org/W2164452299","https://openalex.org/W2164696938","https://openalex.org/W2196956961","https://openalex.org/W2296616510","https://openalex.org/W2400972628","https://openalex.org/W2478708596","https://openalex.org/W2510244936","https://openalex.org/W2950359108","https://openalex.org/W3101990100","https://openalex.org/W4235713725","https://openalex.org/W4250955649","https://openalex.org/W4254714151","https://openalex.org/W4285719527","https://openalex.org/W4300263211"],"related_works":["https://openalex.org/W2378166785","https://openalex.org/W2156466545","https://openalex.org/W2379468505","https://openalex.org/W3104324607","https://openalex.org/W4206981968","https://openalex.org/W1987102304","https://openalex.org/W4285251805","https://openalex.org/W2537887767","https://openalex.org/W1606356673","https://openalex.org/W2601968125"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,48,114,162],"study":[4],"a":[5,160,181,186],"support":[6,60,122,177],"set":[7,61,123,178],"reconstruction":[8,62],"problem":[9],"for":[10,93,98,120,151,175],"multiple":[11],"measurement":[12,78,139],"vectors":[13],"(MMV)":[14],"with":[15,103,106,147,154,167],"different":[16,107,168],"sensing":[17,38,101,108,157,169],"matrices,":[18],"where":[19],"the":[20,41,55,59,66,68,71,75,81,95,112,134,148,155],"signals":[21],"of":[22,43,54,58,65,77,83,136],"interest":[23],"are":[24],"assumed":[25],"to":[26,90,129],"be":[27,88],"jointly":[28],"sparse":[29],"and":[30,51,80,117],"each":[31],"signal":[32],"is":[33],"sampled":[34],"by":[35],"its":[36],"own":[37],"matrix":[39],"in":[40,63,185],"presence":[42],"noise.":[44],"Using":[45],"mathematical":[46],"tools,":[47],"develop":[49,115],"upper":[50],"lower":[52],"bounds":[53,86],"failure":[56],"probability":[57],"terms":[64],"sparsity,":[67],"ambient":[69],"dimension,":[70],"minimum":[72],"signal-to-noise":[73],"ratio,":[74],"number":[76,82],"vectors,":[79],"measurements.":[84],"These":[85],"can":[87],"used":[89],"provide":[91,130],"guidelines":[92],"determining":[94],"system":[96],"parameters":[97],"various":[99],"compressed":[100],"applications":[102],"noisy":[104,152,165],"MMV":[105,153,166],"matrices.":[109],"Based":[110],"on":[111],"bounds,":[113],"necessary":[116],"sufficient":[118,145],"conditions":[119,128],"reliable":[121,176],"reconstruction.":[124],"We":[125,141],"interpret":[126],"these":[127],"theoretical":[131],"explanations":[132],"regarding":[133],"benefits":[135],"taking":[137],"more":[138],"vectors.":[140],"then":[142],"compare":[143],"our":[144],"condition":[146],"existing":[149],"results":[150],"same":[156],"matrix.":[158],"As":[159],"result,":[161],"show":[163],"that":[164],"matrices":[170],"may":[171],"require":[172],"fewer":[173],"measurements":[174],"reconstruction,":[179],"under":[180],"sublinear":[182],"sparsity":[183],"regime":[184],"low":[187],"noise-level":[188],"scenario.":[189]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}