{"id":"https://openalex.org/W1973510848","doi":"https://doi.org/10.1109/tsp.2012.2193392","title":"Compressed Sensing of Complex Sinusoids: An Approach Based on Dictionary Refinement","display_name":"Compressed Sensing of Complex Sinusoids: An Approach Based on Dictionary Refinement","publication_year":2012,"publication_date":"2012-04-12","ids":{"openalex":"https://openalex.org/W1973510848","doi":"https://doi.org/10.1109/tsp.2012.2193392","mag":"1973510848"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2012.2193392","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2012.2193392","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":["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/A5091321590","display_name":"Lei Hu","orcid":"https://orcid.org/0000-0003-3562-9178"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lei Hu","raw_affiliation_strings":["ATR Key Laboratory, National University of Defense Technology, Changsha, Hunan, China","ATR key Lab, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"ATR Key Laboratory, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"ATR key Lab, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102248162","display_name":"Zhiguang Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiguang Shi","raw_affiliation_strings":["ATR Key Laboratory, National University of Defense Technology, Changsha, Hunan, China","ATR key Lab, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"ATR Key Laboratory, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"ATR key Lab, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101813221","display_name":"Jianxiong Zhou","orcid":"https://orcid.org/0000-0002-7800-5173"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxiong Zhou","raw_affiliation_strings":["ATR Key Laboratory, National University of Defense Technology, Changsha, Hunan, China","ATR key Lab, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"ATR Key Laboratory, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"ATR key Lab, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088254630","display_name":"Qiang Fu","orcid":"https://orcid.org/0000-0002-4012-330X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Fu","raw_affiliation_strings":["ATR Key Laboratory, National University of Defense Technology, Changsha, Hunan, China","ATR key Lab, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"ATR Key Laboratory, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"ATR key Lab, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091321590"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":8.0823,"has_fulltext":false,"cited_by_count":105,"citation_normalized_percentile":{"value":0.97994808,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"60","issue":"7","first_page":"3809","last_page":"3822"},"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/T11778","display_name":"Electrical and Bioimpedance Tomography","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9986000061035156,"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/compressed-sensing","display_name":"Compressed sensing","score":0.7812463641166687},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.7593095898628235},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6513444185256958},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6189934611320496},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5511438846588135},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.5230206847190857},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.48968246579170227},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4361934959888458},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41033047437667847},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3641570508480072},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3336228132247925},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3295227885246277}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7812463641166687},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.7593095898628235},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6513444185256958},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6189934611320496},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5511438846588135},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.5230206847190857},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.48968246579170227},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4361934959888458},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41033047437667847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3641570508480072},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3336228132247925},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3295227885246277},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2012.2193392","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2012.2193392","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"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W31037602","https://openalex.org/W1588454411","https://openalex.org/W1633751774","https://openalex.org/W1648445109","https://openalex.org/W1663973292","https://openalex.org/W1848264314","https://openalex.org/W1973233493","https://openalex.org/W1973503417","https://openalex.org/W1985690171","https://openalex.org/W1986931325","https://openalex.org/W1988520084","https://openalex.org/W1998931161","https://openalex.org/W2000721204","https://openalex.org/W2023709806","https://openalex.org/W2023722580","https://openalex.org/W2034260606","https://openalex.org/W2049633694","https://openalex.org/W2057867606","https://openalex.org/W2071284784","https://openalex.org/W2091256848","https://openalex.org/W2101675075","https://openalex.org/W2103519107","https://openalex.org/W2103955025","https://openalex.org/W2109357213","https://openalex.org/W2110767907","https://openalex.org/W2125680629","https://openalex.org/W2127271355","https://openalex.org/W2128633079","https://openalex.org/W2129319777","https://openalex.org/W2129638195","https://openalex.org/W2133285942","https://openalex.org/W2140122025","https://openalex.org/W2145096794","https://openalex.org/W2146509513","https://openalex.org/W2148154358","https://openalex.org/W2151169541","https://openalex.org/W2153187780","https://openalex.org/W2154239231","https://openalex.org/W2164452299","https://openalex.org/W2167604521","https://openalex.org/W2289917018","https://openalex.org/W2296319761","https://openalex.org/W2296616510","https://openalex.org/W2534313802","https://openalex.org/W2963322354","https://openalex.org/W3105340263","https://openalex.org/W3124114587","https://openalex.org/W3125735862","https://openalex.org/W3141391850","https://openalex.org/W4212863985","https://openalex.org/W4250589301","https://openalex.org/W4250955649","https://openalex.org/W4285719527","https://openalex.org/W6601250597","https://openalex.org/W6636690510","https://openalex.org/W6679865946"],"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/W2601968125","https://openalex.org/W2018454463","https://openalex.org/W2537887767"],"abstract_inverted_index":{"In":[0],"the":[1,7,16,23,53,62,71,78,82,88,99,102,108,111,159,164],"existing":[2],"compressed":[3],"sensing":[4],"(CS)":[5],"theory,":[6],"accurate":[8],"reconstruction":[9,47,90,171],"of":[10,18,30,52,101,110,124,142],"an":[11],"unknown":[12],"signal":[13,24,46,89,143,170],"lies":[14],"in":[15,178,182,185],"awareness":[17],"its":[19,93],"sparsifying":[20,41,63,83,135],"dictionary.":[21],"For":[22],"represented":[25],"by":[26,138],"a":[27,39,67,118],"finite":[28],"sum":[29],"complex":[31,125],"sinusoids,":[32],"however,":[33],"it":[34],"is":[35,85],"impractical":[36],"to":[37,45,49,158],"set":[38],"fixed":[40],"Fourier":[42,64],"dictionary":[43,65,84,136,147],"prior":[44],"due":[48],"our":[50],"ignorance":[51],"signal's":[54],"component":[55,190],"frequencies.":[56,191],"To":[57],"address":[58],"this,":[59],"we":[60,116],"model":[61],"as":[66,77],"parameterized":[68],"dictionary,":[69],"with":[70,188],"sampled":[72],"frequency":[73,103],"grid":[74],"points":[75],"treated":[76],"underlying":[79],"parameters.":[80],"Consequently,":[81],"refinable":[86],"during":[87],"process,":[91],"and":[92,134,146,173,184],"refinement":[94,137],"can":[95],"be":[96],"accomplished":[97],"via":[98],"adjustment":[100],"grid.":[104],"Furthermore,":[105],"based":[106],"on":[107],"philosophy":[109],"variational":[112],"expectation-maximization":[113],"(EM)":[114],"algorithm,":[115],"develop":[117],"novel":[119],"recovery":[120,133,162],"algorithm":[121,128,166],"for":[122],"CS":[123,161],"sinusoids.":[126],"The":[127],"achieves":[129,167],"joint":[130],"sparse":[131],"representation":[132],"successively":[139],"executing":[140],"steps":[141],"coefficients":[144],"estimation":[145],"parameters":[148],"optimization.":[149],"Simulation":[150],"results":[151],"under":[152],"different":[153],"conditions":[154],"demonstrate":[155],"that":[156],"compared":[157],"state-of-the-art":[160],"methods,":[163],"proposed":[165],"much":[168],"higher":[169],"accuracy,":[172],"yields":[174],"superior":[175],"performance":[176],"both":[177],"suppressing":[179],"additive":[180],"noise":[181],"measurements":[183],"reconstructing":[186],"signals":[187],"closely-spaced":[189]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":14},{"year":2015,"cited_by_count":14},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":3}],"updated_date":"2026-03-24T08:02:53.985720","created_date":"2025-10-10T00:00:00"}
