{"id":"https://openalex.org/W2972315132","doi":"https://doi.org/10.1109/ijcnn.2019.8851825","title":"Improving Robustness of ReRAM-based Spiking Neural Network Accelerator with Stochastic Spike-timing-dependent-plasticity","display_name":"Improving Robustness of ReRAM-based Spiking Neural Network Accelerator with Stochastic Spike-timing-dependent-plasticity","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2972315132","doi":"https://doi.org/10.1109/ijcnn.2019.8851825","mag":"2972315132"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8851825","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851825","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1909.05401","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032748918","display_name":"Xueyuan She","orcid":"https://orcid.org/0000-0002-7372-5366"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xueyuan She","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA","#N#\u2021#N#Georgia Institute of Technology#N#"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"#N#\u2021#N#Georgia Institute of Technology#N#","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061038190","display_name":"Yun Long","orcid":"https://orcid.org/0000-0003-0627-489X"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yun Long","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA","#N#\u2021#N#Georgia Institute of Technology#N#"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"#N#\u2021#N#Georgia Institute of Technology#N#","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009591041","display_name":"Saibal Mukhopadhyay","orcid":"https://orcid.org/0000-0002-8894-3390"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saibal Mukhopadhyay","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA","#N#\u2021#N#Georgia Institute of Technology#N#"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"#N#\u2021#N#Georgia Institute of Technology#N#","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5032748918"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.1205,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46900618,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2019","issue":null,"first_page":"1","last_page":"8"},"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9994000196456909,"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":0.9990000128746033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.8264119625091553},{"id":"https://openalex.org/keywords/spike-timing-dependent-plasticity","display_name":"Spike-timing-dependent plasticity","score":0.7842249870300293},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7691855430603027},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6755271553993225},{"id":"https://openalex.org/keywords/spike","display_name":"Spike (software development)","score":0.5819839239120483},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5694236159324646},{"id":"https://openalex.org/keywords/resistive-random-access-memory","display_name":"Resistive random-access memory","score":0.4556993246078491},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.44628262519836426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4312354028224945},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.41283851861953735},{"id":"https://openalex.org/keywords/synaptic-plasticity","display_name":"Synaptic plasticity","score":0.20612454414367676},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.0884225070476532},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07372060418128967}],"concepts":[{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.8264119625091553},{"id":"https://openalex.org/C159919123","wikidata":"https://www.wikidata.org/wiki/Q7577157","display_name":"Spike-timing-dependent plasticity","level":4,"score":0.7842249870300293},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7691855430603027},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6755271553993225},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.5819839239120483},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5694236159324646},{"id":"https://openalex.org/C182019814","wikidata":"https://www.wikidata.org/wiki/Q1143830","display_name":"Resistive random-access memory","level":3,"score":0.4556993246078491},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.44628262519836426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4312354028224945},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.41283851861953735},{"id":"https://openalex.org/C98229152","wikidata":"https://www.wikidata.org/wiki/Q1551556","display_name":"Synaptic plasticity","level":3,"score":0.20612454414367676},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0884225070476532},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07372060418128967},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C170493617","wikidata":"https://www.wikidata.org/wiki/Q208467","display_name":"Receptor","level":2,"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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":5,"locations":[{"id":"doi:10.1109/ijcnn.2019.8851825","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851825","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1909.05401","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1909.05401","pdf_url":"https://arxiv.org/pdf/1909.05401","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":"mag:2972315132","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1909.05401","pdf_url":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1909.05401","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1909.05401","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"mag:3048756787","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201902270468506606","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1909.05401","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1909.05401","pdf_url":"https://arxiv.org/pdf/1909.05401","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":[{"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production","score":0.4300000071525574}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306087","display_name":"Semiconductor Research Corporation","ror":"https://ror.org/047z4n946"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2972315132.pdf","grobid_xml":"https://content.openalex.org/works/W2972315132.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W1570411240","https://openalex.org/W1884538784","https://openalex.org/W1964366669","https://openalex.org/W1967628726","https://openalex.org/W1975229527","https://openalex.org/W1977765713","https://openalex.org/W1986246844","https://openalex.org/W1990121607","https://openalex.org/W1993405709","https://openalex.org/W1996088954","https://openalex.org/W1997824093","https://openalex.org/W2009782005","https://openalex.org/W2016922062","https://openalex.org/W2022036926","https://openalex.org/W2032832574","https://openalex.org/W2059148040","https://openalex.org/W2061905891","https://openalex.org/W2063810326","https://openalex.org/W2072233684","https://openalex.org/W2075075476","https://openalex.org/W2082690044","https://openalex.org/W2083407323","https://openalex.org/W2096473662","https://openalex.org/W2103788620","https://openalex.org/W2112739286","https://openalex.org/W2112796928","https://openalex.org/W2113536146","https://openalex.org/W2162827630","https://openalex.org/W2163605009","https://openalex.org/W2178102281","https://openalex.org/W2463288820","https://openalex.org/W2600694480","https://openalex.org/W2798597397","https://openalex.org/W2899749435","https://openalex.org/W2908607580","https://openalex.org/W2944910788","https://openalex.org/W2946047477","https://openalex.org/W3144728138","https://openalex.org/W4236126228","https://openalex.org/W6684191040","https://openalex.org/W6809115935","https://openalex.org/W7023726515"],"related_works":["https://openalex.org/W3108036060","https://openalex.org/W3106704229","https://openalex.org/W3128999834","https://openalex.org/W3198857112","https://openalex.org/W2754845850","https://openalex.org/W3154308428","https://openalex.org/W3096295468","https://openalex.org/W3136463641","https://openalex.org/W3164982922","https://openalex.org/W3126711481","https://openalex.org/W3126994530","https://openalex.org/W2851843155","https://openalex.org/W3203477951","https://openalex.org/W2157335309","https://openalex.org/W3013061921","https://openalex.org/W2994834230","https://openalex.org/W3126449767","https://openalex.org/W3002868444","https://openalex.org/W3001074782","https://openalex.org/W3093460327"],"abstract_inverted_index":{"Spike-timing-dependent-plasticity":[0],"(STDP)":[1],"is":[2,104],"an":[3],"unsupervised":[4],"learning":[5],"algorithm":[6,91,103,127],"for":[7,131],"spiking":[8,94],"neural":[9,63],"network":[10],"(SNN),":[11],"which":[12],"promises":[13],"to":[14,31,97,143],"achieve":[15],"deeper":[16],"understanding":[17],"of":[18,69,76],"human":[19],"brain":[20],"and":[21,49,79,113],"more":[22],"powerful":[23],"artificial":[24],"intelligence.":[25],"While":[26],"conventional":[27],"computing":[28],"system":[29],"fails":[30],"simulate":[32],"SNN":[33,53,137],"efficiently,":[34],"process-in-memory":[35],"(PIM)":[36],"based":[37,52,136],"on":[38],"devices":[39],"such":[40,70],"as":[41,55],"ReRAM":[42,135],"can":[43,128],"be":[44,129],"used":[45,130],"in":[46,58,106],"designing":[47,132],"fast":[48],"efficient":[50],"STDP":[51,90],"accelerators,":[54],"it":[56],"operates":[57],"high":[59],"resemblance":[60],"with":[61,110],"biological":[62],"network.":[64],"However,":[65],"the":[66,125],"real-life":[67],"implementation":[68],"design":[71],"still":[72],"suffers":[73],"from":[74],"impact":[75],"input":[77,112],"noise":[78],"device":[80,144],"variation.":[81,145],"In":[82,120],"this":[83],"work,":[84],"we":[85,122],"present":[86],"a":[87,133],"novel":[88],"stochastic":[89],"that":[92,124,139],"uses":[93],"frequency":[95],"information":[96],"dynamically":[98],"adjust":[99],"synaptic":[100],"behavior.":[101],"The":[102],"tested":[105],"pattern":[107],"recognition":[108],"task":[109],"noisy":[111],"shows":[114],"accuracy":[115],"improvement":[116],"over":[117],"deterministic":[118],"STDP.":[119],"addition,":[121],"show":[123],"new":[126],"robust":[134],"accelerator":[138],"has":[140],"strong":[141],"resilience":[142]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}