{"id":"https://openalex.org/W3000835335","doi":"https://doi.org/10.1109/tim.2020.2969008","title":"Generative Adversarial Networks With Comprehensive Wavelet Feature for Fault Diagnosis of Analog Circuits","display_name":"Generative Adversarial Networks With Comprehensive Wavelet Feature for Fault Diagnosis of Analog Circuits","publication_year":2020,"publication_date":"2020-01-24","ids":{"openalex":"https://openalex.org/W3000835335","doi":"https://doi.org/10.1109/tim.2020.2969008","mag":"3000835335"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2020.2969008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.2969008","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5101414693","display_name":"Wei He","orcid":"https://orcid.org/0000-0002-9289-1888"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei He","raw_affiliation_strings":["School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-9289-1888","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020019416","display_name":"Yigang He","orcid":"https://orcid.org/0000-0002-6642-0740"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]},{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yigang He","raw_affiliation_strings":["School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, China","School of Electrical Engineering, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-6642-0740","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]},{"raw_affiliation_string":"School of Electrical Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100451232","display_name":"Bing Li","orcid":"https://orcid.org/0000-0002-0083-0296"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Li","raw_affiliation_strings":["School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-0083-0296","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.5312,"has_fulltext":false,"cited_by_count":99,"citation_normalized_percentile":{"value":0.96915823,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"69","issue":"9","first_page":"6640","last_page":"6650"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":1.0,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.6874939203262329},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6866703033447266},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.651175320148468},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6418870091438293},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.61868816614151},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5199193358421326},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4941754639148712},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4887673556804657},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4662878215312958},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45420947670936584},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42505255341529846},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.412457138299942},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36826902627944946}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6874939203262329},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6866703033447266},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.651175320148468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6418870091438293},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.61868816614151},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5199193358421326},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4941754639148712},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4887673556804657},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4662878215312958},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45420947670936584},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42505255341529846},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.412457138299942},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36826902627944946},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2020.2969008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.2969008","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6299999952316284,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1396908399","display_name":"\u57fa\u4e8e\u6807\u8bc6\u4f20\u611f\u878d\u5408\u7684\u8f93\u53d8\u7535\u8bbe\u5907\u4fe1\u606f\u611f\u77e5\u4e0e\u5904\u7406\u5173\u952e\u95ee\u9898\u7814\u7a76","funder_award_id":"51637004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2926111433","display_name":null,"funder_award_id":"51777050","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3848853134","display_name":null,"funder_award_id":"51977161","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6496176865","display_name":null,"funder_award_id":"51577046","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7242511093","display_name":null,"funder_award_id":"51977153","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8745910143","display_name":null,"funder_award_id":"2017JJ2080","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1149231055","https://openalex.org/W1492218661","https://openalex.org/W1515595208","https://openalex.org/W1970328656","https://openalex.org/W1999470887","https://openalex.org/W2002106843","https://openalex.org/W2013124207","https://openalex.org/W2087754676","https://openalex.org/W2091076299","https://openalex.org/W2095196047","https://openalex.org/W2099383324","https://openalex.org/W2099471712","https://openalex.org/W2154871109","https://openalex.org/W2163605009","https://openalex.org/W2173520492","https://openalex.org/W2325207965","https://openalex.org/W2412510955","https://openalex.org/W2436151569","https://openalex.org/W2518269126","https://openalex.org/W2528546263","https://openalex.org/W2537309743","https://openalex.org/W2548275288","https://openalex.org/W2562762876","https://openalex.org/W2595657631","https://openalex.org/W2604523962","https://openalex.org/W2754767460","https://openalex.org/W2761781479","https://openalex.org/W2762941833","https://openalex.org/W2763269460","https://openalex.org/W2765284480","https://openalex.org/W2765811365","https://openalex.org/W2776271218","https://openalex.org/W2791006446","https://openalex.org/W2792416274","https://openalex.org/W2795765414","https://openalex.org/W2803978172","https://openalex.org/W2805966918","https://openalex.org/W2897680073","https://openalex.org/W2901123560","https://openalex.org/W2950776302","https://openalex.org/W2952193749","https://openalex.org/W2963684088","https://openalex.org/W4320013936","https://openalex.org/W6684191040","https://openalex.org/W6685352114","https://openalex.org/W6715189028","https://openalex.org/W6729482032"],"related_works":["https://openalex.org/W3040691452","https://openalex.org/W1487808658","https://openalex.org/W3119773509","https://openalex.org/W3208297503","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W156213964","https://openalex.org/W2050960118","https://openalex.org/W4388405611","https://openalex.org/W2619127353"],"abstract_inverted_index":{"Analog":[0],"circuits":[1],"are":[2,230],"one":[3],"of":[4,75,91,134,160,168,183,195,204,221,237,243],"the":[5,37,54,60,64,72,76,85,89,92,119,124,128,138,142,153,161,165,169,175,180,184,187,193,201,205,211,218,234,238,251],"most":[6],"commonly":[7],"used":[8,82],"components":[9],"in":[10],"industrial":[11],"equipment.":[12],"Circuit":[13],"failure":[14,185],"may":[15],"lead":[16],"to":[17,70,83,108,213,232],"significant":[18],"causalities":[19],"and":[20,41,95,127,164,186,225],"even":[21],"enormous":[22],"financial":[23],"losses.":[24],"To":[25],"cope":[26],"with":[27,88,131,217,246],"this":[28],"problem,":[29],"a":[30,99,214],"novel":[31],"deep":[32],"learning":[33],"strategy":[34],"based":[35],"on":[36,63,104,137],"cross-wavelet":[38],"transform":[39],"(XWT)":[40],"generative":[42,162],"adversarial":[43,157],"networks":[44,229],"(GANs)":[45],"is":[46,68,102,198],"proposed":[47,154,239,252],"for":[48,145,257],"analog-circuit":[49,258],"fault":[50,77,147,259],"diagnosis.":[51,260],"Different":[52],"from":[53],"traditional":[55],"methods":[56,248],"that":[57,79,197,250],"simply":[58],"apply":[59],"amplitude":[61],"characteristic":[62],"time-frequency":[65,139],"plane,":[66],"XWT":[67],"applied":[69],"obtain":[71],"spectral":[73,106],"images":[74,107,112],"signals":[78,126],"can":[80,117,149,171],"be":[81,150],"capture":[84],"comprehensive":[86],"features":[87],"involvement":[90],"amplitude,":[93],"phase,":[94],"coherence":[96],"characteristics.":[97],"Furthermore,":[98,208],"data-regularization":[100],"trick":[101],"employed":[103],"these":[105],"construct":[109],"three-channel":[110],"feature":[111,129],"data.":[113],"The":[114,156,241],"input":[115],"data":[116],"reflect":[118],"complex":[120,176],"relationship":[121,178],"effectively":[122],"between":[123,179],"measured":[125],"space,":[130],"abundant":[132],"information":[133],"multiple":[135],"domains":[136],"plane.":[140],"Finally,":[141],"different":[143],"distributions":[144],"various":[146],"conditions":[148],"learned":[151],"by":[152,200],"GAN.":[155],"training":[158,206],"manner":[159],"network":[163,167],"discriminative":[166],"GAN":[170,212],"not":[172],"only":[173],"mine":[174],"nonlinear":[177],"root":[181],"cause":[182],"signal":[188],"signature":[189],"but":[190],"also":[191],"alleviate":[192],"problem":[194],"overfitting":[196],"caused":[199],"limited":[202],"availability":[203],"samples.":[207],"we":[209],"expand":[210],"supervised":[215],"classifier":[216],"coordinative":[219],"usage":[220],"two":[222,226],"auxiliary":[223],"classifiers,":[224],"convolution":[227],"neural":[228],"adopted":[231],"establish":[233],"basic":[235],"structure":[236],"model.":[240],"comparisons":[242],"classification":[244],"performance":[245],"other":[247],"indicate":[249],"approach":[253],"has":[254],"good":[255],"potential":[256]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":6}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2025-10-10T00:00:00"}