{"id":"https://openalex.org/W3157046588","doi":"https://doi.org/10.1109/tvlsi.2021.3069221","title":"Competitive Neural Network Circuit Based on Winner-Take-All Mechanism and Online Hebbian Learning Rule","display_name":"Competitive Neural Network Circuit Based on Winner-Take-All Mechanism and Online Hebbian Learning Rule","publication_year":2021,"publication_date":"2021-04-26","ids":{"openalex":"https://openalex.org/W3157046588","doi":"https://doi.org/10.1109/tvlsi.2021.3069221","mag":"3157046588"},"language":"en","primary_location":{"id":"doi:10.1109/tvlsi.2021.3069221","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvlsi.2021.3069221","pdf_url":null,"source":{"id":"https://openalex.org/S37538908","display_name":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","issn_l":"1063-8210","issn":["1063-8210","1557-9999"],"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 Very Large Scale Integration (VLSI) Systems","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/A5027732281","display_name":"Zhuojun Chen","orcid":"https://orcid.org/0000-0003-0431-8852"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhuojun Chen","raw_affiliation_strings":["College of Physics and Electronics, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Physics and Electronics, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033606806","display_name":"Judi Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Judi Zhang","raw_affiliation_strings":["College of Physics and Electronics, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Physics and Electronics, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029464464","display_name":"Shuangchun Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuangchun Wen","raw_affiliation_strings":["College of Physics and Electronics, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Physics and Electronics, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100343657","display_name":"Ya Li","orcid":"https://orcid.org/0000-0002-3351-7909"},"institutions":[{"id":"https://openalex.org/I4210122543","display_name":"Guangdong Polytechnic Normal University","ror":"https://ror.org/02pcb5m77","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210122543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ya Li","raw_affiliation_strings":["College of Electronics and Information, Guangdong Polytechnic Normal University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Electronics and Information, Guangdong Polytechnic Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I4210122543"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052210009","display_name":"Qinghui Hong","orcid":"https://orcid.org/0000-0002-6210-6033"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghui Hong","raw_affiliation_strings":["College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5027732281"],"corresponding_institution_ids":["https://openalex.org/I16609230"],"apc_list":null,"apc_paid":null,"fwci":1.5158,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.82119151,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"29","issue":"6","first_page":"1095","last_page":"1107"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","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/T10502","display_name":"Advanced Memory and Neural Computing","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/T10581","display_name":"Neural dynamics and brain function","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hebbian-theory","display_name":"Hebbian theory","score":0.8887922167778015},{"id":"https://openalex.org/keywords/winner-take-all","display_name":"Winner-take-all","score":0.737513542175293},{"id":"https://openalex.org/keywords/memristor","display_name":"Memristor","score":0.7158928513526917},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7019573450088501},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6289334893226624},{"id":"https://openalex.org/keywords/competitive-learning","display_name":"Competitive learning","score":0.5814857482910156},{"id":"https://openalex.org/keywords/learning-rule","display_name":"Learning rule","score":0.48620671033859253},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41775667667388916},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36283451318740845},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.2698320746421814},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20615154504776}],"concepts":[{"id":"https://openalex.org/C111437709","wikidata":"https://www.wikidata.org/wiki/Q1277874","display_name":"Hebbian theory","level":3,"score":0.8887922167778015},{"id":"https://openalex.org/C168976158","wikidata":"https://www.wikidata.org/wiki/Q769931","display_name":"Winner-take-all","level":3,"score":0.737513542175293},{"id":"https://openalex.org/C150072547","wikidata":"https://www.wikidata.org/wiki/Q212923","display_name":"Memristor","level":2,"score":0.7158928513526917},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7019573450088501},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6289334893226624},{"id":"https://openalex.org/C120822770","wikidata":"https://www.wikidata.org/wiki/Q5156355","display_name":"Competitive learning","level":3,"score":0.5814857482910156},{"id":"https://openalex.org/C2779127903","wikidata":"https://www.wikidata.org/wiki/Q6510194","display_name":"Learning rule","level":3,"score":0.48620671033859253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41775667667388916},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36283451318740845},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.2698320746421814},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20615154504776}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvlsi.2021.3069221","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvlsi.2021.3069221","pdf_url":null,"source":{"id":"https://openalex.org/S37538908","display_name":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","issn_l":"1063-8210","issn":["1063-8210","1557-9999"],"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 Very Large Scale Integration (VLSI) Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G193743341","display_name":null,"funder_award_id":"2019JJ50092","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"},{"id":"https://openalex.org/G2702146854","display_name":null,"funder_award_id":"531118010418","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5690989117","display_name":null,"funder_award_id":"62001163","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7506489240","display_name":null,"funder_award_id":"61804053","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"},{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W1676218289","https://openalex.org/W1976342705","https://openalex.org/W1996388323","https://openalex.org/W2003619715","https://openalex.org/W2008901850","https://openalex.org/W2112181056","https://openalex.org/W2132563832","https://openalex.org/W2162651880","https://openalex.org/W2260028708","https://openalex.org/W2312652241","https://openalex.org/W2513917688","https://openalex.org/W2525649597","https://openalex.org/W2603064927","https://openalex.org/W2727726870","https://openalex.org/W2800329759","https://openalex.org/W2800653266","https://openalex.org/W2806177657","https://openalex.org/W2807205556","https://openalex.org/W2810542477","https://openalex.org/W2887655043","https://openalex.org/W2904302621","https://openalex.org/W2906048113","https://openalex.org/W2919129235","https://openalex.org/W2922008207","https://openalex.org/W2942096054","https://openalex.org/W2944434490","https://openalex.org/W2963883579","https://openalex.org/W2965799887","https://openalex.org/W2968114889","https://openalex.org/W2969551671","https://openalex.org/W2971734772","https://openalex.org/W2972686555","https://openalex.org/W2973530122","https://openalex.org/W2979256949","https://openalex.org/W2989683650","https://openalex.org/W2990695486","https://openalex.org/W3001813906","https://openalex.org/W3003078125","https://openalex.org/W3003821665","https://openalex.org/W3011601585","https://openalex.org/W3013325484","https://openalex.org/W3014166398","https://openalex.org/W3014493180","https://openalex.org/W3018413598","https://openalex.org/W3020626027","https://openalex.org/W3022676494","https://openalex.org/W3027014941","https://openalex.org/W3027492159","https://openalex.org/W3029952621","https://openalex.org/W3030670306","https://openalex.org/W3035236698","https://openalex.org/W3074061299","https://openalex.org/W3081140267","https://openalex.org/W3102808035","https://openalex.org/W3104804488","https://openalex.org/W3117114592","https://openalex.org/W6736339276"],"related_works":["https://openalex.org/W1597526543","https://openalex.org/W3157046588","https://openalex.org/W2183231132","https://openalex.org/W1520894008","https://openalex.org/W1530541224","https://openalex.org/W2150516419","https://openalex.org/W2088600489","https://openalex.org/W4210762357","https://openalex.org/W2035995768","https://openalex.org/W2131254613"],"abstract_inverted_index":{"In":[0,71,116],"this":[1,72],"article,":[2,73],"we":[3,196],"design":[4,104],"a":[5,162,168,185],"memristive":[6],"competitive":[7,59,238],"neural":[8,60,153,239],"network":[9,27,61,154,230,240],"circuit":[10,62,80,155,192],"based":[11,83,111],"on":[12,84,112,190],"the":[13,18,26,44,54,74,79,85,91,98,106,124,143,147,159,178,191,198,215,219,224,229,245],"winner-take-all":[14],"(WTA)":[15],"mechanism":[16],"and":[17,48,68,95,173,184,218,233],"online":[19],"Hebbian":[20,113],"learning":[21,114],"rule.":[22],"Each":[23],"synapse":[24],"of":[25,33,78,90,101,105,146,161,180,200,212,248],"contains":[28],"two":[29,64],"memristors":[30,121],"whose":[31],"terminals":[32],"signal":[34],"inputs":[35],"are":[36],"opposite.":[37],"However,":[38],"only":[39,119],"one":[40,50],"memristor":[41,139],"participates":[42],"in":[43,128,194,214,223],"calculation":[45,67,76,130],"each":[46,117],"time,":[47],"that":[49,228],"is":[51,81,110],"determined":[52],"by":[53],"original":[55],"input":[56],"signal.":[57],"The":[58,88,103,134,151,209,237],"includes":[63],"parts:":[65],"forward":[66,75,129],"weight":[69,107],"update.":[70],"part":[77,109],"designed":[82,193],"WTA":[86],"mechanism.":[87],"combination":[89],"leaky-integrate-and-fire":[92],"(LIF)":[93],"model":[94],"pMOS":[96],"realizes":[97,175],"lateral":[99],"inhibition":[100],"neurons.":[102],"updating":[108],"rules.":[115],"cycle,":[118],"synaptic":[120,138],"connected":[122],"to":[123,244],"winner":[125,148],"output":[126,149],"neuron":[127],"can":[131,231,241],"be":[132,242],"adjusted.":[133],"voltage":[135,145],"used":[136],"for":[137],"adjustment":[140],"comes":[141],"from":[142],"membrane":[144],"neuron.":[150],"whole":[152],"does":[156],"not":[157],"need":[158],"participation":[160],"central":[163],"processing":[164],"unit":[165],"(CPU)":[166],"or":[167],"field-programmable":[169],"gate":[170],"array":[171],"(FPGA)":[172],"really":[174],"parallel":[176],"calculation,":[177],"saving":[179],"area,":[181],"power":[182],"consumption,":[183],"certain":[186],"extent":[187],"computing-in-memory.":[188],"Based":[189],"PSPICE,":[195],"simulated":[197],"classification":[199],"<inline-formula":[201],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[202],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[203],"<tex-math":[204],"notation=\"LaTeX\">$5\\times3$":[205],"</tex-math></inline-formula>":[206],"pixel":[207],"pictures.":[208],"changing":[210],"trend":[211],"weights":[213],"training":[216],"phase":[217,226],"high":[220],"recognition":[221,225],"accuracy":[222],"prove":[227],"learn":[232],"recognize":[234],"different":[235],"patterns.":[236],"applied":[243],"neuromorphic":[246],"system":[247],"visual":[249],"pattern":[250],"recognition.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}