{"id":"https://openalex.org/W2622142618","doi":"https://doi.org/10.1109/vlsi-dat.2017.7939642","title":"Hybrid spiking-stochastic Deep Neural Network","display_name":"Hybrid spiking-stochastic Deep Neural Network","publication_year":2017,"publication_date":"2017-04-01","ids":{"openalex":"https://openalex.org/W2622142618","doi":"https://doi.org/10.1109/vlsi-dat.2017.7939642","mag":"2622142618"},"language":"en","primary_location":{"id":"doi:10.1109/vlsi-dat.2017.7939642","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vlsi-dat.2017.7939642","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)","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/A5103130858","display_name":"Heesu Kim","orcid":"https://orcid.org/0000-0002-5822-7019"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Heesu Kim","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102372265","display_name":"Joonsang Yu","orcid":"https://orcid.org/0000-0002-9165-0572"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Joonsang Yu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043594476","display_name":"Ki\u2010Young Choi","orcid":"https://orcid.org/0000-0001-6138-6697"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kiyoung Choi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103130858"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":0.1433,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49015272,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"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":0.9983000159263611,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9940000176429749,"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/stochastic-computing","display_name":"Stochastic computing","score":0.9054282903671265},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.816960334777832},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.6577988862991333},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6528193950653076},{"id":"https://openalex.org/keywords/stochastic-neural-network","display_name":"Stochastic neural network","score":0.6468973159790039},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.5866128206253052},{"id":"https://openalex.org/keywords/power-consumption","display_name":"Power consumption","score":0.48787474632263184},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4795377254486084},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4448704719543457},{"id":"https://openalex.org/keywords/stochastic-process","display_name":"Stochastic process","score":0.4323377013206482},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30779391527175903},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.27924174070358276},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.24487298727035522},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08652636408805847}],"concepts":[{"id":"https://openalex.org/C2780971903","wikidata":"https://www.wikidata.org/wiki/Q2933705","display_name":"Stochastic computing","level":3,"score":0.9054282903671265},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.816960334777832},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.6577988862991333},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6528193950653076},{"id":"https://openalex.org/C86582703","wikidata":"https://www.wikidata.org/wiki/Q7617824","display_name":"Stochastic neural network","level":4,"score":0.6468973159790039},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.5866128206253052},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.48787474632263184},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4795377254486084},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4448704719543457},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.4323377013206482},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30779391527175903},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.27924174070358276},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.24487298727035522},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08652636408805847},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vlsi-dat.2017.7939642","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vlsi-dat.2017.7939642","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8899999856948853}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322091","display_name":"Korea Institute of Science and Technology","ror":"https://ror.org/05kzfa883"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1645800954","https://openalex.org/W1825672851","https://openalex.org/W1980178290","https://openalex.org/W2003056114","https://openalex.org/W2152839228","https://openalex.org/W2294282016","https://openalex.org/W2402098947","https://openalex.org/W2954145425","https://openalex.org/W2962804204","https://openalex.org/W2963157821","https://openalex.org/W4294371482","https://openalex.org/W6638839971","https://openalex.org/W6697189835"],"related_works":["https://openalex.org/W2908853553","https://openalex.org/W3127981342","https://openalex.org/W2927803337","https://openalex.org/W4322624379","https://openalex.org/W4294000389","https://openalex.org/W2769932825","https://openalex.org/W3012119183","https://openalex.org/W2787602342","https://openalex.org/W4287864703","https://openalex.org/W3006958873"],"abstract_inverted_index":{"Stochastic":[0],"computing":[1,23,32,65],"has":[2,33,104],"been":[3],"adopted":[4],"in":[5],"various":[6],"fields":[7],"to":[8,55,90],"improve":[9,56],"the":[10,27,57,70,83,88,91,96,105,119],"power":[11,28,115],"efficiency":[12],"of":[13,36,59,72,107,122],"systems.":[14],"Recent":[15],"work":[16],"showed":[17],"that":[18],"DNN":[19,60,103],"based":[20,62],"on":[21,63],"stochastic":[22,31,64],"can":[24],"greatly":[25],"reduce":[26],"consumption.":[29],"However,":[30],"a":[34,52,78,100],"limitation":[35],"high":[37],"latency":[38,58,112],"overhead":[39],"as":[40,82],"it":[41,68],"computes":[42],"values":[43],"only":[44],"one":[45],"bit":[46],"per":[47],"cycle.":[48],"This":[49],"paper":[50],"proposes":[51],"new":[53],"scheme":[54],"implementation":[61],"by":[66],"combining":[67],"with":[69],"concept":[71],"spiking":[73,79],"neural":[74,80,93],"networks.":[75],"It":[76],"uses":[77],"network":[81,94],"front":[84],"end":[85],"and":[86,113],"pipeline":[87],"results":[89],"stochastic-computing":[92],"at":[95],"back":[97],"end.":[98],"Such":[99],"hybrid":[101],"spiking-stochastic":[102],"benefits":[106],"both":[108],"approaches":[109],"including":[110],"low":[111,114],"consumption,":[116],"while":[117],"maintaining":[118],"same":[120],"level":[121],"accuracy.":[123]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
