{"id":"https://openalex.org/W3083076704","doi":"https://doi.org/10.1109/jiot.2020.3021724","title":"Deep Unfolding With Weighted <i>\u2113</i>\u2082 Minimization for Compressive Sensing","display_name":"Deep Unfolding With Weighted <i>\u2113</i>\u2082 Minimization for Compressive Sensing","publication_year":2020,"publication_date":"2020-09-04","ids":{"openalex":"https://openalex.org/W3083076704","doi":"https://doi.org/10.1109/jiot.2020.3021724","mag":"3083076704"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2020.3021724","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2020.3021724","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","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/A5100433227","display_name":"Jun Zhang","orcid":"https://orcid.org/0000-0002-9647-0941"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jun Zhang","raw_affiliation_strings":["School of Information Engineering, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100672536","display_name":"Yuanqing Li","orcid":"https://orcid.org/0000-0003-4288-5591"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanqing Li","raw_affiliation_strings":["College of Automation Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108367651","display_name":"Zhu Liang Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhu Liang Yu","raw_affiliation_strings":["College of Automation Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048899636","display_name":"Zhenghui Gu","orcid":"https://orcid.org/0000-0001-9365-2953"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenghui Gu","raw_affiliation_strings":["College of Automation Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022741226","display_name":"Yu Cheng","orcid":"https://orcid.org/0000-0001-6717-5727"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Cheng","raw_affiliation_strings":["School of Information Engineering, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001845701","display_name":"Huoqing Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huoqing Gong","raw_affiliation_strings":["School of Information Engineering, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100433227"],"corresponding_institution_ids":["https://openalex.org/I139024713"],"apc_list":null,"apc_paid":null,"fwci":2.2888,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.87625702,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"8","issue":"4","first_page":"3027","last_page":"3041"},"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T10727","display_name":"Ultrasound Imaging and Elastography","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.9245153665542603},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7810181379318237},{"id":"https://openalex.org/keywords/undersampling","display_name":"Undersampling","score":0.7699719667434692},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7494550347328186},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.5934153199195862},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5290421843528748},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5097693800926208},{"id":"https://openalex.org/keywords/prior-information","display_name":"Prior information","score":0.5052130818367004},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48506274819374084},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.45215392112731934},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42390117049217224},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3967417776584625},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30647313594818115},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.2861784100532532},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.09257206320762634}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.9245153665542603},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7810181379318237},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.7699719667434692},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7494550347328186},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.5934153199195862},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5290421843528748},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5097693800926208},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.5052130818367004},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48506274819374084},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.45215392112731934},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42390117049217224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3967417776584625},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30647313594818115},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2861784100532532},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.09257206320762634},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"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/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/jiot.2020.3021724","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2020.3021724","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3346253610","display_name":null,"funder_award_id":"61973088","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G351089225","display_name":null,"funder_award_id":"91120305","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4242704309","display_name":null,"funder_award_id":"61836003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5471918313","display_name":null,"funder_award_id":"61573152","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1576445103","https://openalex.org/W1831449718","https://openalex.org/W1978749115","https://openalex.org/W2014311222","https://openalex.org/W2018990310","https://openalex.org/W2030449718","https://openalex.org/W2041046019","https://openalex.org/W2065321782","https://openalex.org/W2071284784","https://openalex.org/W2075506710","https://openalex.org/W2078204800","https://openalex.org/W2097073572","https://openalex.org/W2100526560","https://openalex.org/W2107861471","https://openalex.org/W2111394763","https://openalex.org/W2112041273","https://openalex.org/W2116261113","https://openalex.org/W2118103795","https://openalex.org/W2125680629","https://openalex.org/W2126607811","https://openalex.org/W2127455914","https://openalex.org/W2129131372","https://openalex.org/W2129334939","https://openalex.org/W2129638195","https://openalex.org/W2133665775","https://openalex.org/W2134033146","https://openalex.org/W2146000945","https://openalex.org/W2150224753","https://openalex.org/W2163398148","https://openalex.org/W2163654892","https://openalex.org/W2165548826","https://openalex.org/W2219727625","https://openalex.org/W2247338144","https://openalex.org/W2273561594","https://openalex.org/W2296616510","https://openalex.org/W2468144468","https://openalex.org/W2470117147","https://openalex.org/W2509600863","https://openalex.org/W2551814208","https://openalex.org/W2552808051","https://openalex.org/W2556806401","https://openalex.org/W2578009003","https://openalex.org/W2596951540","https://openalex.org/W2609901723","https://openalex.org/W2619204584","https://openalex.org/W2619210453","https://openalex.org/W2746816686","https://openalex.org/W2762625016","https://openalex.org/W2774622533","https://openalex.org/W2794923494","https://openalex.org/W2798559986","https://openalex.org/W2803531409","https://openalex.org/W2806956350","https://openalex.org/W2807140035","https://openalex.org/W2890736047","https://openalex.org/W2901363489","https://openalex.org/W2913407974","https://openalex.org/W2963676935","https://openalex.org/W2964167436","https://openalex.org/W3102722370","https://openalex.org/W4250955649","https://openalex.org/W4297801963","https://openalex.org/W6631943919","https://openalex.org/W6634343353","https://openalex.org/W6677645113","https://openalex.org/W6729455701"],"related_works":["https://openalex.org/W2212041357","https://openalex.org/W2895530314","https://openalex.org/W3011226087","https://openalex.org/W1959447026","https://openalex.org/W2052082011","https://openalex.org/W2903019797","https://openalex.org/W2218273114","https://openalex.org/W2378166785","https://openalex.org/W2156466545","https://openalex.org/W2308961925"],"abstract_inverted_index":{"Compressive":[0],"sensing":[1],"(CS)":[2],"aims":[3],"to":[4,52,86],"accurately":[5],"reconstruct":[6],"high-dimensional":[7],"signals":[8,49],"from":[9,133],"a":[10,61,99,151],"small":[11],"number":[12],"of":[13,48,65,90,123],"measurements":[14],"by":[15,94,150],"exploiting":[16],"signal":[17,23],"sparsity":[18],"and":[19,146],"structural":[20,46],"priors.":[21],"However,":[22],"priors":[24,47,82,116],"utilized":[25],"in":[26,55],"existing":[27],"CS":[28,68],"reconstruction":[29,69],"algorithms":[30],"rely":[31],"mainly":[32],"on":[33,157],"hand-crafted":[34],"design,":[35],"which":[36,79],"often":[37],"cannot":[38],"offer":[39],"the":[40,66,87,91,95,104,124,127,138,155,158],"best":[41],"sparsity-undersampling":[42],"tradeoff":[43],"because":[44],"high-order":[45],"are":[50],"hard":[51],"be":[53,131],"captured":[54],"this":[56,59],"manner.":[57],"In":[58],"article,":[60],"new":[62],"recovery":[63],"guarantee":[64],"unified":[67],"model-weighted":[70],"\u2113":[71],"<sub":[72],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[73],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[74],"minimization":[75],"(WL1M)":[76],"is":[77],"derived,":[78],"indicates":[80],"universal":[81,115],"could":[83],"hardly":[84],"lead":[85],"optimal":[88],"selection":[89],"weights.":[92],"Motivated":[93],"analysis,":[96],"we":[97],"propose":[98],"deep":[100,110,147],"unfolding":[101],"network":[102],"for":[103],"general":[105],"WL1M":[106,112],"model.":[107],"The":[108],"proposed":[109,139],"unfolding-based":[111],"(D-WL1M)":[113],"integrates":[114],"with":[117],"learning":[118],"capability":[119],"so":[120],"that":[121],"all":[122],"parameters,":[125],"including":[126],"crucial":[128],"weights,":[129],"can":[130],"learned":[132],"training":[134],"data.":[135],"We":[136],"demonstrate":[137],"D-WL1M":[140],"outperforms":[141],"several":[142],"state-of-the-art":[143],"CS-based":[144],"methods":[145,149],"learning-based":[148],"large":[152],"margin":[153],"via":[154],"experiments":[156],"Caltech-256":[159],"image":[160],"data":[161],"set.":[162]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}