{"id":"https://openalex.org/W4236949603","doi":"https://doi.org/10.1109/isicir.2014.7029565","title":"Energy efficient spiking neural network design with RRAM devices","display_name":"Energy efficient spiking neural network design with RRAM devices","publication_year":2014,"publication_date":"2014-12-01","ids":{"openalex":"https://openalex.org/W4236949603","doi":"https://doi.org/10.1109/isicir.2014.7029565"},"language":"en","primary_location":{"id":"doi:10.1109/isicir.2014.7029565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isicir.2014.7029565","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Symposium on Integrated Circuits (ISIC)","raw_type":"proceedings-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/A5101663599","display_name":"Tianqi Tang","orcid":"https://orcid.org/0000-0001-8255-985X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianqi Tang","raw_affiliation_strings":["Dept. of E.E., Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. of E.E., Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101846193","display_name":"Rong Luo","orcid":"https://orcid.org/0000-0003-1062-598X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Luo","raw_affiliation_strings":["Dept. of E.E., Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. of E.E., Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085347958","display_name":"Boxun Li","orcid":"https://orcid.org/0000-0002-7026-6723"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boxun Li","raw_affiliation_strings":["Dept. of E.E., Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. of E.E., Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100429403","display_name":"Hai Li","orcid":"https://orcid.org/0000-0003-3228-6544"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hai Li","raw_affiliation_strings":["Dept. of E.C.E., University of Pittsburgh, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of E.C.E., University of Pittsburgh, Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445061","display_name":"Yu Wang","orcid":"https://orcid.org/0000-0001-6108-5157"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Wang","raw_affiliation_strings":["Dept. of E.E., Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. of E.E., Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023755254","display_name":"Huazhong Yang","orcid":"https://orcid.org/0000-0003-2421-353X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huazhong Yang","raw_affiliation_strings":["Dept. of E.E., Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. of E.E., Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101663599"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.6385,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.76104055,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"3","issue":null,"first_page":"268","last_page":"271"},"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":0.9980000257492065,"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/T12236","display_name":"Photoreceptor and optogenetics research","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular 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":0.8789433240890503},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.8562265634536743},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.8106225728988647},{"id":"https://openalex.org/keywords/resistive-random-access-memory","display_name":"Resistive random-access memory","score":0.7467393279075623},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.746566891670227},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5501818656921387},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5297331213951111},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.4426164925098419},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.19769683480262756},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14223405718803406},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.06730273365974426}],"concepts":[{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.8789433240890503},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.8562265634536743},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.8106225728988647},{"id":"https://openalex.org/C182019814","wikidata":"https://www.wikidata.org/wiki/Q1143830","display_name":"Resistive random-access memory","level":3,"score":0.7467393279075623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.746566891670227},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5501818656921387},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5297331213951111},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.4426164925098419},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.19769683480262756},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14223405718803406},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.06730273365974426}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/isicir.2014.7029565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isicir.2014.7029565","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Symposium on Integrated Circuits (ISIC)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.711.3385","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.711.3385","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://nicsefc.ee.tsinghua.edu.cn/media/publications/2014/ISIC14_31.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8999999761581421}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1486852018","https://openalex.org/W1498101568","https://openalex.org/W1512746852","https://openalex.org/W1976075132","https://openalex.org/W1998683499","https://openalex.org/W2003619715","https://openalex.org/W2006370340","https://openalex.org/W2007815184","https://openalex.org/W2018774711","https://openalex.org/W2028868915","https://openalex.org/W2142796540","https://openalex.org/W2157239334","https://openalex.org/W2334364695","https://openalex.org/W4233317171","https://openalex.org/W4238869234","https://openalex.org/W4292169167","https://openalex.org/W6630758646"],"related_works":["https://openalex.org/W4281699635","https://openalex.org/W4321472116","https://openalex.org/W3202619090","https://openalex.org/W3102040318","https://openalex.org/W4287724471","https://openalex.org/W2786930404","https://openalex.org/W3214713078","https://openalex.org/W2944910788","https://openalex.org/W3035000326","https://openalex.org/W3041589219"],"abstract_inverted_index":{"The":[0,12,77,91],"brain-inspired":[1],"neural":[2,14,46,71,103,115],"networks":[3],"have":[4],"demonstrated":[5],"great":[6,27],"potential":[7],"in":[8,29,54],"big":[9],"data":[10,22,53],"analysis.":[11],"spiking":[13,70,102],"network":[15,47,72,104,116],"(SNN),":[16],"which":[17,49],"encodes":[18],"the":[19,43,51,94,99],"real":[20],"world":[21],"into":[23],"spike":[24],"trains,":[25],"promises":[26],"performance":[28],"computational":[30],"ability":[31],"and":[32,80,87],"energy":[33,65],"efficiency.":[34],"Moreover,":[35],"it":[36],"is":[37],"much":[38],"more":[39],"biologically":[40],"plausible":[41],"than":[42],"traditional":[44,88],"artificial":[45,114],"(ANN),":[48],"keeps":[50],"input":[52],"its":[55],"original":[56],"form.":[57],"In":[58],"this":[59],"paper,":[60],"we":[61],"introduce":[62],"an":[63],"RRAM-based":[64,101,113],"efficient":[66],"implementation":[67],"of":[68,108],"STDP-based":[69],"cascaded":[73],"with":[74,112,117],"ANN":[75],"classifier.":[76],"recognition":[78],"accuracy":[79,120],"power":[81,109],"consumption":[82,110],"are":[83],"compared":[84,111],"between":[85],"SNN":[86],"three-layer":[89],"ANN.":[90],"experiments":[92],"on":[93],"MNIST":[95],"database":[96],"demonstrate":[97],"that":[98],"proposed":[100],"requires":[105],"only":[106],"14%":[107],"a":[118],"slight":[119],"decay":[121],"(~2%).":[122]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}