{"id":"https://openalex.org/W2755193401","doi":"https://doi.org/10.1109/nanoarch.2017.8053708","title":"Spatio-temporal learning with arrays of analog nanosynapses","display_name":"Spatio-temporal learning with arrays of analog nanosynapses","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2755193401","doi":"https://doi.org/10.1109/nanoarch.2017.8053708","mag":"2755193401"},"language":"en","primary_location":{"id":"doi:10.1109/nanoarch.2017.8053708","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nanoarch.2017.8053708","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH)","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/1709.03849","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088323080","display_name":"Christopher H. Bennett","orcid":"https://orcid.org/0000-0002-6989-292X"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I102197404","display_name":"Universit\u00e9 Paris-Sud","ror":"https://ror.org/028rypz17","country_code":"FR","type":"education","lineage":["https://openalex.org/I102197404"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Christopher H. Bennett","raw_affiliation_strings":["C2N, Univ. Paris-Saclay, CNRS, Orsay, France","C2N, Univ. Paris-Saclay, Universite Paris-Sud, CNRS, 91405 Orsay, France"],"affiliations":[{"raw_affiliation_string":"C2N, Univ. Paris-Saclay, CNRS, Orsay, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"C2N, Univ. Paris-Saclay, Universite Paris-Sud, CNRS, 91405 Orsay, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I102197404","https://openalex.org/I1294671590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063819347","display_name":"Damien Querlioz","orcid":"https://orcid.org/0000-0002-0295-1008"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I102197404","display_name":"Universit\u00e9 Paris-Sud","ror":"https://ror.org/028rypz17","country_code":"FR","type":"education","lineage":["https://openalex.org/I102197404"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Damien Querlioz","raw_affiliation_strings":["C2N, Univ. Paris-Saclay, CNRS, Orsay, France","C2N, Univ. Paris-Saclay, Universite Paris-Sud, CNRS, 91405 Orsay, France"],"affiliations":[{"raw_affiliation_string":"C2N, Univ. Paris-Saclay, CNRS, Orsay, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"C2N, Univ. Paris-Saclay, Universite Paris-Sud, CNRS, 91405 Orsay, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I102197404","https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102978184","display_name":"Jacques\u2010Olivier Klein","orcid":"https://orcid.org/0000-0002-6923-5276"},"institutions":[{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I102197404","display_name":"Universit\u00e9 Paris-Sud","ror":"https://ror.org/028rypz17","country_code":"FR","type":"education","lineage":["https://openalex.org/I102197404"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jacques-Olivier Klein","raw_affiliation_strings":["C2N, Univ. Paris-Saclay, CNRS, Orsay, France","C2N, Univ. Paris-Saclay, Universite Paris-Sud, CNRS, 91405 Orsay, France"],"affiliations":[{"raw_affiliation_string":"C2N, Univ. Paris-Saclay, CNRS, Orsay, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"C2N, Univ. Paris-Saclay, Universite Paris-Sud, CNRS, 91405 Orsay, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I102197404","https://openalex.org/I1294671590"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5088323080"],"corresponding_institution_ids":["https://openalex.org/I102197404","https://openalex.org/I1294671590","https://openalex.org/I277688954"],"apc_list":null,"apc_paid":null,"fwci":0.26427781,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59752948,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"125","last_page":"130"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"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":0.9998999834060669,"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/T12676","display_name":"Machine Learning and ELM","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9980000257492065,"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/mnist-database","display_name":"MNIST database","score":0.938673734664917},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7918766736984253},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.5299828052520752},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5166168808937073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5075899362564087},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.47385290265083313},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4623165726661682},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.4469722807407379},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44375038146972656},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.42733487486839294},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34998106956481934},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3445799946784973},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16524353623390198}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.938673734664917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7918766736984253},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.5299828052520752},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5166168808937073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5075899362564087},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.47385290265083313},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4623165726661682},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4469722807407379},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44375038146972656},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.42733487486839294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34998106956481934},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3445799946784973},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16524353623390198},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/nanoarch.2017.8053708","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nanoarch.2017.8053708","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1709.03849","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.03849","pdf_url":"https://arxiv.org/pdf/1709.03849","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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.1709.03849","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1709.03849","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:2755193401","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1709.03849","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.03849","pdf_url":"https://arxiv.org/pdf/1709.03849","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":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9100000262260437,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2755193401.pdf","grobid_xml":"https://content.openalex.org/works/W2755193401.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W61757119","https://openalex.org/W1480485976","https://openalex.org/W1542488308","https://openalex.org/W1575051237","https://openalex.org/W1982296198","https://openalex.org/W1986964674","https://openalex.org/W1988401319","https://openalex.org/W2018774711","https://openalex.org/W2028868915","https://openalex.org/W2031878488","https://openalex.org/W2046404756","https://openalex.org/W2081126728","https://openalex.org/W2083357246","https://openalex.org/W2097228199","https://openalex.org/W2103179919","https://openalex.org/W2111072639","https://openalex.org/W2112796928","https://openalex.org/W2113132555","https://openalex.org/W2123321612","https://openalex.org/W2138913040","https://openalex.org/W2156640153","https://openalex.org/W2515601391","https://openalex.org/W2559718113","https://openalex.org/W2591029953","https://openalex.org/W2963356011","https://openalex.org/W6606804413","https://openalex.org/W6694319147","https://openalex.org/W6695833955"],"related_works":["https://openalex.org/W3189972411","https://openalex.org/W3203150477","https://openalex.org/W2802994863","https://openalex.org/W3184526936","https://openalex.org/W2267244539","https://openalex.org/W3202875595","https://openalex.org/W3161328488","https://openalex.org/W3126606986","https://openalex.org/W2739515247","https://openalex.org/W2896722540","https://openalex.org/W2947616034","https://openalex.org/W3039982286","https://openalex.org/W2767979715","https://openalex.org/W2765161362","https://openalex.org/W2888429796","https://openalex.org/W3157992795","https://openalex.org/W2072223598","https://openalex.org/W3048691934","https://openalex.org/W3014565582","https://openalex.org/W2733236492"],"abstract_inverted_index":{"Emerging":[0],"nanodevices":[1],"such":[2],"as":[3,30],"resistive":[4],"memories":[5],"are":[6],"being":[7],"considered":[8],"for":[9],"hardware":[10],"realizations":[11],"of":[12,15,25,65,110,144],"a":[13,94,100,138,187],"variety":[14],"artificial":[16],"neural":[17],"networks":[18],"(ANNs),":[19],"including":[20],"highly":[21,95],"promising":[22],"online":[23],"variants":[24],"the":[26,35,62,85,107,133,141,149,152,175],"learning":[27,37,45],"approaches":[28],"known":[29],"reservoir":[31],"computing":[32],"(RC)":[33],"and":[34,55,71,87,155,181],"extreme":[36],"machine":[38],"(ELM).":[39],"We":[40,83],"propose":[41],"an":[42,170],"RC/ELM":[43],"inspired":[44],"system":[46,67,86,114,189],"built":[47],"with":[48,76,93,103,128,190],"nanosynapses":[49],"that":[50,197],"performs":[51],"both":[52],"on-chip":[53],"projection":[54],"regression":[56],"operations.":[57],"To":[58],"address":[59],"time-dynamic":[60],"tasks,":[61],"hidden":[63,122],"neurons":[64],"our":[66],"perform":[68],"spatio-temporal":[69],"integration":[70,158],"can":[72,182],"be":[73,184],"further":[74],"enhanced":[75],"variable":[77,157],"sampling":[78],"or":[79],"multiple":[80],"activation":[81],"windows.":[82],"detail":[84],"show":[88],"its":[89],"use":[90],"in":[91,193],"conjunction":[92],"analog":[96],"nanosynapse":[97],"device":[98],"on":[99],"standard":[101],"task":[102],"intrinsic":[104],"timing":[105],"dynamics-":[106],"TI-46":[108],"battery":[109],"spoken":[111],"digits.":[112,146],"The":[113],"achieves":[115],"nearly":[116],"perfect":[117],"(99%)":[118],"accuracy":[119,164],"at":[120],"sufficient":[121],"layer":[123],"size,":[124],"which":[125],"compares":[126],"favorably":[127],"software":[129],"results.":[130],"In":[131,167],"addition,":[132],"model":[134],"is":[135,165],"extended":[136],"to":[137,161,169],"larger":[139],"dataset,":[140],"MNIST":[142],"database":[143,150],"handwritten":[145],"By":[147],"translating":[148],"into":[151,186],"time":[153],"domain":[154],"using":[156],"windows,":[159],"up":[160],"95%":[162],"classification":[163],"achieved.":[166],"addition":[168],"intrinsically":[171],"low-power":[172],"programming":[173],"style,":[174],"proposed":[176],"architecture":[177],"learns":[178],"very":[179],"quickly":[180],"easily":[183],"converted":[185],"spiking":[188],"negligible":[191],"loss":[192],"performance-":[194],"all":[195],"features":[196],"confer":[198],"significant":[199],"energy":[200],"efficiency.":[201]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}