{"id":"https://openalex.org/W4402557564","doi":"https://doi.org/10.1109/jiot.2024.3462544","title":"Meta-Learning Guided Label Noise Distillation for Robust Signal Modulation Classification","display_name":"Meta-Learning Guided Label Noise Distillation for Robust Signal Modulation Classification","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4402557564","doi":"https://doi.org/10.1109/jiot.2024.3462544"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2024.3462544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3462544","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/A5035603089","display_name":"Xiaoyang Hao","orcid":"https://orcid.org/0000-0002-6062-841X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyang Hao","raw_affiliation_strings":["School of Artificial Intelligence, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-6062-841X","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053487344","display_name":"Zhixi Feng","orcid":"https://orcid.org/0000-0002-7372-9180"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixi Feng","raw_affiliation_strings":["School of Artificial Intelligence, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-7372-9180","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049173148","display_name":"Tongqing Peng","orcid":"https://orcid.org/0000-0003-1349-3724"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongqing Peng","raw_affiliation_strings":["School of Artificial Intelligence, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0003-1349-3724","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100764373","display_name":"Shuyuan Yang","orcid":"https://orcid.org/0000-0002-4796-5737"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuyuan Yang","raw_affiliation_strings":["School of Artificial Intelligence, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-4796-5737","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.503,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.96751285,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9710999727249146,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9710999727249146,"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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9648000001907349,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9089999794960022,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7483402490615845},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5879747271537781},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5382596850395203},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5061408877372742},{"id":"https://openalex.org/keywords/modulation","display_name":"Modulation (music)","score":0.4955681562423706},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.49331679940223694},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4726996421813965},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.44101861119270325},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.43131470680236816},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4193042516708374},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41898012161254883},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.1257629692554474},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12075731158256531},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.09338042140007019},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.08927670121192932}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7483402490615845},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5879747271537781},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5382596850395203},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5061408877372742},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.4955681562423706},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.49331679940223694},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4726996421813965},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.44101861119270325},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.43131470680236816},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4193042516708374},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41898012161254883},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.1257629692554474},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12075731158256531},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.09338042140007019},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.08927670121192932},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2024.3462544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3462544","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/G7804021936","display_name":null,"funder_award_id":"U22B2018,61771376, 61771380, 61836009","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":54,"referenced_works":["https://openalex.org/W2120019163","https://openalex.org/W2147893740","https://openalex.org/W2167460663","https://openalex.org/W2170778725","https://openalex.org/W2272847350","https://openalex.org/W2566079294","https://openalex.org/W2603396821","https://openalex.org/W2734908518","https://openalex.org/W2741230443","https://openalex.org/W2773170971","https://openalex.org/W2957915633","https://openalex.org/W2961044345","https://openalex.org/W2963697299","https://openalex.org/W2964292098","https://openalex.org/W2983220838","https://openalex.org/W2999862233","https://openalex.org/W3004724178","https://openalex.org/W3016147814","https://openalex.org/W3022121429","https://openalex.org/W3034197595","https://openalex.org/W3047492485","https://openalex.org/W3060435609","https://openalex.org/W3085631338","https://openalex.org/W3098755434","https://openalex.org/W3123268700","https://openalex.org/W3164063707","https://openalex.org/W4210557982","https://openalex.org/W4225308684","https://openalex.org/W4225727763","https://openalex.org/W4225766285","https://openalex.org/W4226117432","https://openalex.org/W4285106632","https://openalex.org/W4285238813","https://openalex.org/W4286255690","https://openalex.org/W4293195393","https://openalex.org/W4312300932","https://openalex.org/W4312766345","https://openalex.org/W4321483861","https://openalex.org/W4323338327","https://openalex.org/W4324291272","https://openalex.org/W4379983761","https://openalex.org/W4385212083","https://openalex.org/W4385938100","https://openalex.org/W4386634503","https://openalex.org/W4390357259","https://openalex.org/W4390481140","https://openalex.org/W4390659928","https://openalex.org/W4392543825","https://openalex.org/W4393147307","https://openalex.org/W6747898760","https://openalex.org/W6751420435","https://openalex.org/W6751647823","https://openalex.org/W6771630921","https://openalex.org/W6846971969"],"related_works":["https://openalex.org/W3026162553","https://openalex.org/W2768175398","https://openalex.org/W2344382886","https://openalex.org/W19111321","https://openalex.org/W2412887479","https://openalex.org/W32245304","https://openalex.org/W2953684491","https://openalex.org/W4285338581","https://openalex.org/W4308823735","https://openalex.org/W2787240389"],"abstract_inverted_index":{"Automatic":[0],"modulation":[1],"classification":[2],"(AMC)":[3],"has":[4],"a":[5,55,77,95,108,138,206],"wide":[6],"range":[7],"of":[8,20,45,66,111,148],"applications":[9],"in":[10,36,174],"both":[11],"civilian":[12],"and":[13,27,43,84,104,119,161,172,185,217],"military":[14,28],"fields,":[15],"such":[16],"as":[17],"industrial":[18],"Internet":[19],"Things":[21],"(IIoT)":[22],"security,":[23],"communication":[24],"spectrum":[25],"management,":[26],"electronic":[29],"countermeasures.":[30],"However,":[31],"label":[32,58,70,86,179,187,215,225,234],"mislabeling":[33],"often":[34],"occurs":[35],"practical":[37],"scenarios,":[38,181],"significantly":[39,169],"impacting":[40],"the":[41,64,89,129,146,159,193,199],"performance":[42,147],"robustness":[44,65,173,231],"deep":[46],"neural":[47,196],"networks":[48],"(DNNs).":[49],"In":[50],"this":[51],"article,":[52],"we":[53,75,136],"propose":[54,76,137],"meta-learning":[56],"guided":[57],"noise":[59,71,180,216,235],"distillation":[60],"method":[61,142],"to":[62,82,125,143,192,209,219,232,238],"enhance":[63,145],"AMC":[67,176],"models":[68],"against":[69],"or":[72],"errors.":[73],"Specifically,":[74],"teacher-student":[78],"heterogeneous":[79],"network":[80,131,197],"(TSHN)":[81],"discriminate":[83],"distill":[85],"noise.":[87,188,226],"Following":[88],"notion":[90],"that":[91,166],"labels":[92,106],"represent":[93],"information,":[94],"teacher":[96],"network,":[97],"utilizing":[98],"trusted":[99,153],"few-shot":[100,152],"labeled":[101,113,122,154],"samples,":[102],"reevaluates":[103],"corrects":[105],"for":[107],"considerable":[109],"number":[110],"untrusted":[112,121],"samples":[114,123],"through":[115],"meta-learning.":[116],"By":[117],"dividing":[118],"conquering":[120],"according":[124],"their":[126],"confidence":[127],"levels,":[128],"student":[130],"learns":[132],"more":[133],"effectively.":[134],"Additionally,":[135],"multiview":[139],"signal":[140,175],"(MVS)":[141],"further":[144],"hard-to-classify":[149],"categories":[150],"with":[151,198],"samples.":[155],"Extensive":[156],"experiments":[157],"on":[158],"RadioML2016":[160],"HisarMod2019.1":[162],"data":[163],"sets":[164],"demonstrate":[165],"our":[167,202],"methods":[168],"improve":[170],"accuracy":[171,211,221],"across":[177],"diverse":[178],"including":[182],"symmetric,":[183],"asymmetric,":[184],"mixed":[186,224],"For":[189],"example,":[190],"compared":[191,237],"baseline":[194],"convolutional":[195],"cross-entropy":[200],"loss,":[201],"proposed":[203],"TSHN":[204,228],"achieves":[205],"remarkable":[207],"1.26%":[208],"36.84%":[210],"improvement":[212,222],"under":[213,223],"symmetric":[214],"0.12%":[218],"38.59%":[220],"Moreover,":[227],"exhibits":[229],"greater":[230],"varying":[233],"rates":[236],"existing":[239],"methods.":[240]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}