{"id":"https://openalex.org/W2980241036","doi":"https://doi.org/10.1109/lsp.2019.2945683","title":"Joint Design of Measurement Matrix and Sparse Support Recovery Method via Deep Auto-Encoder","display_name":"Joint Design of Measurement Matrix and Sparse Support Recovery Method via Deep Auto-Encoder","publication_year":2019,"publication_date":"2019-10-07","ids":{"openalex":"https://openalex.org/W2980241036","doi":"https://doi.org/10.1109/lsp.2019.2945683","mag":"2980241036"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2019.2945683","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2945683","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1910.04330","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050011835","display_name":"Shuaichao Li","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuaichao Li","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118983748","display_name":"Wanqing Zhang","orcid":"https://orcid.org/0000-0001-5046-360X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanqing Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071987706","display_name":"Ying Cui","orcid":"https://orcid.org/0000-0003-3181-9775"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Cui","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-3181-9775","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081375588","display_name":"Hei Victor Cheng","orcid":"https://orcid.org/0000-0001-8432-3779"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hei Victor Cheng","raw_affiliation_strings":["University of Toronto, Toronto, Canada"],"raw_orcid":"https://orcid.org/0000-0001-8432-3779","affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004681822","display_name":"Wei Yu","orcid":"https://orcid.org/0000-0002-7453-422X"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wei Yu","raw_affiliation_strings":["University of Toronto, Toronto, Canada"],"raw_orcid":"https://orcid.org/0000-0002-7453-422X","affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.7267,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.98312752,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"26","issue":"12","first_page":"1778","last_page":"1782"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9994000196456909,"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":0.9991999864578247,"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/computer-science","display_name":"Computer science","score":0.8294928073883057},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6771303415298462},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6038314700126648},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5857603549957275},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5125329494476318},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49511781334877014},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.48420313000679016},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.472737193107605},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.43290793895721436},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.43274497985839844},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4282422661781311},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4233153164386749},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4148634374141693},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4045184850692749},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.33723723888397217},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.191091388463974},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.15358394384384155},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1128489077091217}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8294928073883057},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6771303415298462},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6038314700126648},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5857603549957275},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5125329494476318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49511781334877014},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.48420313000679016},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.472737193107605},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.43290793895721436},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.43274497985839844},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4282422661781311},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4233153164386749},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4148634374141693},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4045184850692749},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.33723723888397217},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.191091388463974},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.15358394384384155},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1128489077091217},{"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/lsp.2019.2945683","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2945683","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1910.04330","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.04330","pdf_url":"https://arxiv.org/pdf/1910.04330","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-161210","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-161210","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1910.04330","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.04330","pdf_url":"https://arxiv.org/pdf/1910.04330","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1674742109","https://openalex.org/W1987371344","https://openalex.org/W1987415890","https://openalex.org/W2004696306","https://openalex.org/W2118103795","https://openalex.org/W2127300249","https://openalex.org/W2135046866","https://openalex.org/W2138019504","https://openalex.org/W2141556672","https://openalex.org/W2171787095","https://openalex.org/W2507344106","https://openalex.org/W2578009003","https://openalex.org/W2624606293","https://openalex.org/W2706056020","https://openalex.org/W2784331297","https://openalex.org/W2912027531","https://openalex.org/W2914401487","https://openalex.org/W2945125725","https://openalex.org/W2950634328","https://openalex.org/W2963145597","https://openalex.org/W2963728985","https://openalex.org/W2964121744","https://openalex.org/W2964315752","https://openalex.org/W2964322393","https://openalex.org/W3098083265","https://openalex.org/W3134059753","https://openalex.org/W4288365549","https://openalex.org/W6631190155","https://openalex.org/W6651560236","https://openalex.org/W6677645113","https://openalex.org/W6758705071","https://openalex.org/W6759377846","https://openalex.org/W6762113363","https://openalex.org/W6762186144"],"related_works":["https://openalex.org/W2026015445","https://openalex.org/W2095407248","https://openalex.org/W1997714924","https://openalex.org/W2129190845","https://openalex.org/W4389045637","https://openalex.org/W1994209155","https://openalex.org/W2076843925","https://openalex.org/W4384300015","https://openalex.org/W2054979592","https://openalex.org/W2100712766"],"abstract_inverted_index":{"Sparse":[0],"support":[1,16,51,120],"recovery":[2,17,52,121],"arises":[3],"in":[4,7,60,136,165,171],"many":[5],"applications":[6],"communications":[8,144],"and":[9,24,50,71,99],"signal":[10],"processing.":[11],"Existing":[12],"methods":[13],"tackle":[14],"sparse":[15,56,119],"problems":[18],"for":[19,33,54,86,140],"a":[20,41,72],"given":[21],"measurement":[22,48],"matrix,":[23],"cannot":[25],"flexibly":[26],"exploit":[27,94],"the":[28,47,114,150,166],"properties":[29,95,106],"of":[30,96,168],"sparsity":[31,97,172],"patterns":[32],"improving":[34],"performance.":[35],"In":[36,112],"this":[37],"letter,":[38],"we":[39],"propose":[40],"data-driven":[42],"approach":[43,91,116,152],"to":[44],"jointly":[45],"design":[46],"matrix":[49],"method":[53],"complex":[55,81],"signals,":[57],"using":[58,83],"auto-encoder":[59,70,78,85],"deep":[61],"learning.":[62],"The":[63,76,89],"proposed":[64,77,90,115,151],"architecture":[65],"includes":[66],"two":[67],"components,":[68],"an":[69,130],"hard":[73],"thresholding":[74],"module.":[75],"successfully":[79],"handles":[80],"signals":[82],"standard":[84],"real":[87],"numbers.":[88],"can":[92,117],"effectively":[93],"patterns,":[98],"is":[100],"especially":[101],"useful":[102],"when":[103],"these":[104],"underlying":[105],"do":[107],"not":[108],"have":[109],"analytic":[110],"models.":[111],"addition,":[113],"achieve":[118],"with":[122,157],"low":[123],"computational":[124],"complexity.":[125],"Experiments":[126],"are":[127],"conducted":[128],"on":[129],"application":[131],"example,":[132],"device":[133],"activity":[134],"detection":[135],"grant-free":[137],"massive":[138,141],"access":[139],"machine":[142],"type":[143],"(mMTC).":[145],"Numerical":[146],"results":[147],"show":[148],"that":[149],"achieves":[153],"significantly":[154],"better":[155],"performance":[156],"much":[158],"less":[159],"computation":[160],"time":[161],"than":[162],"classic":[163],"methods,":[164],"presence":[167],"extra":[169],"structures":[170],"patterns.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":17},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2020-11-23T00:00:00"}
