{"id":"https://openalex.org/W3088225538","doi":"https://doi.org/10.1109/tcsii.2020.3024912","title":"2-D Learned Proximal Gradient Algorithm for Fast Sparse Matrix Recovery","display_name":"2-D Learned Proximal Gradient Algorithm for Fast Sparse Matrix Recovery","publication_year":2020,"publication_date":"2020-09-18","ids":{"openalex":"https://openalex.org/W3088225538","doi":"https://doi.org/10.1109/tcsii.2020.3024912","mag":"3088225538"},"language":"en","primary_location":{"id":"doi:10.1109/tcsii.2020.3024912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsii.2020.3024912","pdf_url":null,"source":{"id":"https://openalex.org/S93916849","display_name":"IEEE Transactions on Circuits & Systems II Express Briefs","issn_l":"1549-7747","issn":["1549-7747","1558-3791"],"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 Circuits and Systems II: Express Briefs","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/A5045874995","display_name":"C. N. Yang","orcid":"https://orcid.org/0000-0002-0529-1367"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengzhu Yang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100621681","display_name":"Yuantao Gu","orcid":"https://orcid.org/0000-0002-8427-1021"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuantao Gu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077852542","display_name":"Badong Chen","orcid":"https://orcid.org/0000-0003-1710-3818"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Badong Chen","raw_affiliation_strings":["Institute of Artificial Intelligence and Robotics, Xi\u2019an Jiaotong University, Xi\u2019an, China","Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Robotics, Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075551339","display_name":"Hongbing Ma","orcid":"https://orcid.org/0000-0002-1785-4024"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongbing Ma","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082563150","display_name":"Hing Cheung So","orcid":"https://orcid.org/0000-0001-8396-7898"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Hing Cheung So","raw_affiliation_strings":["City University of Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0499,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.73019549,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"68","issue":"4","first_page":"1492","last_page":"1496"},"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":0.9987999796867371,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9983000159263611,"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":0.6747919917106628},{"id":"https://openalex.org/keywords/signal-recovery","display_name":"Signal recovery","score":0.673771321773529},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.6678588390350342},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.664462685585022},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6574368476867676},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6108404994010925},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.576651394367218},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.539036750793457},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.42670929431915283},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4220721125602722},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4171258807182312},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3099340796470642},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.08281901478767395},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.08087453246116638}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6747919917106628},{"id":"https://openalex.org/C2989281035","wikidata":"https://www.wikidata.org/wiki/Q120811","display_name":"Signal recovery","level":3,"score":0.673771321773529},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.6678588390350342},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.664462685585022},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6574368476867676},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6108404994010925},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.576651394367218},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.539036750793457},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.42670929431915283},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4220721125602722},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4171258807182312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3099340796470642},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.08281901478767395},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.08087453246116638},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsii.2020.3024912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsii.2020.3024912","pdf_url":null,"source":{"id":"https://openalex.org/S93916849","display_name":"IEEE Transactions on Circuits & Systems II Express Briefs","issn_l":"1549-7747","issn":["1549-7747","1558-3791"],"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 Circuits and Systems II: Express Briefs","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6788006064","display_name":"\u57fa\u4e8e\u5b50\u7a7a\u95f4\u805a\u7c7b\u7684\u9c81\u68d2\u9ad8\u65af\u6df7\u5408\u6a21\u578b\u53c2\u6570\u4f30\u8ba1\u7814\u7a76","funder_award_id":"61971266","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7659680391","display_name":null,"funder_award_id":"2017YFC0403600","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8140084985","display_name":null,"funder_award_id":"N_CityU 104/15","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"},{"id":"https://openalex.org/G98108051","display_name":null,"funder_award_id":"61531166005","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321592","display_name":"Research Grants Council, University Grants Committee","ror":"https://ror.org/00djwmt25"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1904938324","https://openalex.org/W1987090397","https://openalex.org/W2001380973","https://openalex.org/W2003571173","https://openalex.org/W2074577749","https://openalex.org/W2100068253","https://openalex.org/W2100556411","https://openalex.org/W2103115408","https://openalex.org/W2104783034","https://openalex.org/W2118103795","https://openalex.org/W2142225600","https://openalex.org/W2154231875","https://openalex.org/W2289145899","https://openalex.org/W2346728112","https://openalex.org/W2586224208","https://openalex.org/W2619204584","https://openalex.org/W2763081248","https://openalex.org/W2889134685","https://openalex.org/W2963371269","https://openalex.org/W2964121744","https://openalex.org/W2969770677","https://openalex.org/W4297791549","https://openalex.org/W6631190155","https://openalex.org/W6677645113","https://openalex.org/W6682433143","https://openalex.org/W6704980600","https://openalex.org/W6754103055"],"related_works":["https://openalex.org/W1502442302","https://openalex.org/W2087326866","https://openalex.org/W2118132594","https://openalex.org/W2078389543","https://openalex.org/W3024569604","https://openalex.org/W2023089748","https://openalex.org/W2136676913","https://openalex.org/W3005946484","https://openalex.org/W3029251452","https://openalex.org/W2737338842"],"abstract_inverted_index":{"Many":[0],"real-world":[1],"problems":[2],"can":[3,40,91],"be":[4,41],"modeled":[5],"as":[6,17],"sparse":[7,94],"matrix":[8,47],"recovery":[9],"from":[10,29],"two-dimensional":[11],"(2D)":[12],"measurements,":[13],"which":[14,69],"is":[15],"recognized":[16],"one":[18],"of":[19,33,84,106],"the":[20,30,74,82,85,93,104,107],"most":[21],"important":[22],"topics":[23],"in":[24],"signal":[25,95],"processing":[26],"community.":[27],"Benefited":[28],"roaring":[31],"success":[32],"compressed":[34],"sensing,":[35],"many":[36],"classical":[37,112],"iterative":[38],"algorithms":[39],"directly":[42],"applied":[43],"or":[44],"reinvented":[45],"for":[46],"recovery,":[48],"though":[49],"they":[50],"are":[51],"computationally":[52],"expensive.":[53],"To":[54],"alleviate":[55],"this,":[56],"we":[57],"propose":[58],"a":[59],"neural":[60],"network":[61,86],"named":[62],"2D":[63],"learned":[64],"proximal":[65],"gradient":[66],"algorithm":[67],"(2D-LPGA),":[68],"aims":[70],"to":[71],"quickly":[72],"reconstruct":[73,92],"target":[75],"matrix.":[76],"Theoretical":[77],"analysis":[78],"reveals":[79],"that":[80],"if":[81],"parameters":[83],"satisfy":[87],"certain":[88],"conditions,":[89],"it":[90],"with":[96],"linear":[97],"convergence":[98],"rate.":[99],"Moreover,":[100],"numerical":[101],"experiments":[102],"demonstrate":[103],"superiority":[105],"proposed":[108],"method":[109],"over":[110],"other":[111],"schemes.":[113]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
