{"id":"https://openalex.org/W4383501627","doi":"https://doi.org/10.1109/aicas57966.2023.10168617","title":"Validation of a CMOS SNN network based on a time-domain threshold neuron circuit achieving 114.90 pJ/inference on MNIST","display_name":"Validation of a CMOS SNN network based on a time-domain threshold neuron circuit achieving 114.90 pJ/inference on MNIST","publication_year":2023,"publication_date":"2023-06-11","ids":{"openalex":"https://openalex.org/W4383501627","doi":"https://doi.org/10.1109/aicas57966.2023.10168617"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/aicas57966.2023.10168617","pdf_url":null,"source":{"id":"https://openalex.org/S4363608281","display_name":"2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS)","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":false},"type":"article","type_crossref":"proceedings-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/A5020993652","display_name":"Diego Soto Garc\u00eda","orcid":null},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Diego Garcia","raw_affiliation_strings":["Electronic Tech. Dept., Carlos III University, Leganes, Spain"],"affiliations":[{"raw_affiliation_string":"Electronic Tech. Dept., Carlos III University, Leganes, Spain","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012809180","display_name":"Javier Granizo","orcid":"https://orcid.org/0000-0002-0857-862X"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Javier Granizo","raw_affiliation_strings":["Electronic Tech. Dept., Carlos III University, Leganes, Spain"],"affiliations":[{"raw_affiliation_string":"Electronic Tech. Dept., Carlos III University, Leganes, Spain","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100614402","display_name":"Luis Hern\u00e1ndez","orcid":"https://orcid.org/0000-0002-0433-2032"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Luis Hernandez","raw_affiliation_strings":["Electronic Tech. Dept., Carlos III University, Leganes, Spain"],"affiliations":[{"raw_affiliation_string":"Electronic Tech. Dept., Carlos III University, Leganes, Spain","institution_ids":["https://openalex.org/I50357001"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.519,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.547354,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":79,"max":85},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":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":0.9995,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9994,"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":0.89617383},{"id":"https://openalex.org/keywords/biological-neuron-model","display_name":"Biological neuron model","score":0.49884868}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.89617383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6917878},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.5981258},{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.55716234},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.51413065},{"id":"https://openalex.org/C186565885","wikidata":"https://www.wikidata.org/wiki/Q1651163","display_name":"Biological neuron model","level":3,"score":0.49884868},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44962934},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43774134},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.41144478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37982556},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13724831},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/aicas57966.2023.10168617","pdf_url":null,"source":{"id":"https://openalex.org/S4363608281","display_name":"2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS)","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":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.46,"id":"https://metadata.un.org/sdg/7"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":16,"referenced_works":["https://openalex.org/W2097579177","https://openalex.org/W2112796928","https://openalex.org/W2135046866","https://openalex.org/W2183631084","https://openalex.org/W2549653513","https://openalex.org/W2744357319","https://openalex.org/W2783525259","https://openalex.org/W2900282770","https://openalex.org/W2984844508","https://openalex.org/W3201870057","https://openalex.org/W3207233952","https://openalex.org/W4221164624","https://openalex.org/W4225834143","https://openalex.org/W4294691375","https://openalex.org/W4296079226","https://openalex.org/W4321015223"],"related_works":["https://openalex.org/W4386227043","https://openalex.org/W4321472116","https://openalex.org/W4287724471","https://openalex.org/W4281699635","https://openalex.org/W3214713078","https://openalex.org/W3202619090","https://openalex.org/W3161396968","https://openalex.org/W3102040318","https://openalex.org/W3035000326","https://openalex.org/W2786930404"],"abstract_inverted_index":{"This":[0,35],"paper":[1],"proves":[2],"the":[3,16,32,43,51,59,69,73,93,107,120],"computing":[4],"capability":[5],"of":[6,15,50,90],"a":[7,23,37,64,111],"recently":[8],"proposed":[9],"spiking":[10,81],"neuron":[11,17,54],"circuit.":[12],"The":[13,53],"novelty":[14],"resides":[18],"in":[19,22],"being":[20],"based":[21],"subthreshold-operated":[24],"ring":[25],"oscillator":[26],"that":[27,84],"is":[28,55,76,114,117],"indirectly":[29],"powered":[30],"by":[31],"input":[33],"spikes.":[34],"allows":[36],"very":[38],"efficient":[39],"power":[40,109],"usage.":[41],"In":[42],"paper,":[44],"we":[45],"derive":[46],"an":[47,80,105],"analytical":[48,60,74],"model":[49,61,70,75],"neuron.":[52],"then":[56],"co-simulated":[57],"using":[58],"along":[62],"with":[63,119],"transistor-level":[65],"circuit":[66],"to":[67,78,88],"check":[68],"accuracy.":[71],"Afterward,":[72],"used":[77],"construct":[79],"neural":[82],"network":[83],"can":[85],"be":[86],"trained":[87],"98%":[89],"accuracy":[91],"on":[92],"MNIST":[94],"data":[95],"set,":[96],"proving":[97],"equivalent":[98],"performance":[99],"than":[100],"other":[101],"contemporary":[102],"circuits.":[103],"As":[104],"advantage,":[106],"estimated":[108],"for":[110],"LeNet-5":[112],"implementation":[113],"114.90pJ/inference,":[115],"which":[116],"competitive":[118],"state-of-the-art.":[121]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4383501627","counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2024-12-09T05:46:55.013918","created_date":"2023-07-08"}