{"id":"https://openalex.org/W2007698311","doi":"https://doi.org/10.1109/biocas.2013.6679626","title":"An on-chip learning, low-power probabilistic spiking neural network with long-term memory","display_name":"An on-chip learning, low-power probabilistic spiking neural network with long-term memory","publication_year":2013,"publication_date":"2013-10-01","ids":{"openalex":"https://openalex.org/W2007698311","doi":"https://doi.org/10.1109/biocas.2013.6679626","mag":"2007698311"},"language":"en","primary_location":{"id":"doi:10.1109/biocas.2013.6679626","is_oa":false,"landing_page_url":"https://doi.org/10.1109/biocas.2013.6679626","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Biomedical Circuits and Systems Conference (BioCAS)","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/A5084075889","display_name":"Hung-Yi Hsieh","orcid":null},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Hung-Yi Hsieh","raw_affiliation_strings":["Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan, ROC","Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan, ROC","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan#TAB#","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044259295","display_name":"Kea\u2010Tiong Tang","orcid":"https://orcid.org/0000-0002-9689-1236"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Kea-Tiong Tang","raw_affiliation_strings":["Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan, ROC","Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan, ROC","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan#TAB#","institution_ids":["https://openalex.org/I25846049"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5084075889"],"corresponding_institution_ids":["https://openalex.org/I25846049"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.07703104,"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":"5","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/T10320","display_name":"Neural Networks and Applications","score":0.9965999722480774,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.996399998664856,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.7826625108718872},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7465671896934509},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7276089191436768},{"id":"https://openalex.org/keywords/cmos","display_name":"CMOS","score":0.6033885478973389},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5714957118034363},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.5210439562797546},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.492766410112381},{"id":"https://openalex.org/keywords/power-consumption","display_name":"Power consumption","score":0.4784103333950043},{"id":"https://openalex.org/keywords/probabilistic-neural-network","display_name":"Probabilistic neural network","score":0.42807066440582275},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.42443645000457764},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.3847985863685608},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35593053698539734},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3398188352584839},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.33318662643432617},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.28289544582366943},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.19275233149528503},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16878721117973328},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09235730767250061}],"concepts":[{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.7826625108718872},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7465671896934509},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7276089191436768},{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.6033885478973389},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5714957118034363},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.5210439562797546},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.492766410112381},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.4784103333950043},{"id":"https://openalex.org/C134342201","wikidata":"https://www.wikidata.org/wiki/Q7246859","display_name":"Probabilistic neural network","level":4,"score":0.42807066440582275},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.42443645000457764},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3847985863685608},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35593053698539734},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3398188352584839},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.33318662643432617},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.28289544582366943},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.19275233149528503},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16878721117973328},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09235730767250061},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/biocas.2013.6679626","is_oa":false,"landing_page_url":"https://doi.org/10.1109/biocas.2013.6679626","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Biomedical Circuits and Systems Conference (BioCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8799999952316284,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321040","display_name":"National Science Council","ror":"https://ror.org/02kv4zf79"},{"id":"https://openalex.org/F4320322410","display_name":"MediaTek","ror":"https://ror.org/05g9jck81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1992526734","https://openalex.org/W1994918405","https://openalex.org/W1997261908","https://openalex.org/W2028166238","https://openalex.org/W2062317815","https://openalex.org/W2103507131","https://openalex.org/W2104410938","https://openalex.org/W2110376488","https://openalex.org/W2124909604","https://openalex.org/W2148730974","https://openalex.org/W2163288878"],"related_works":["https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W3032952384","https://openalex.org/W3034302643","https://openalex.org/W1847088711","https://openalex.org/W4225394202","https://openalex.org/W3036642985","https://openalex.org/W2964335273","https://openalex.org/W2982145560","https://openalex.org/W3127981342"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"an":[3],"analog":[4],"probabilistic":[5],"spiking":[6],"neural":[7,90],"network":[8],"(PSNN)":[9],"circuit":[10,37,50],"for":[11,74],"portable":[12],"and":[13,23,32],"implanted":[14],"applications":[15],"which":[16],"especially":[17],"require":[18],"low":[19],"power,":[20],"small":[21],"area":[22],"on-chip":[24],"learning":[25],"to":[26],"ensure":[27],"good":[28],"mobility,":[29],"body":[30],"safety":[31],"continually":[33],"accurate":[34],"classification.":[35],"The":[36],"is":[38,92],"implemented":[39],"using":[40],"TSMC":[41],"0.18\u03bcm":[42],"CMOS":[43],"technology.":[44],"Simulation":[45],"results":[46],"show":[47],"that":[48],"the":[49,84],"can":[51],"learn":[52],"linearly":[53],"non-separable":[54],"exclusive-or":[55],"(xor)":[56],"problem":[57],"under":[58],"1V":[59],"supply":[60],"with":[61,87],"only":[62],"3.8\u03bcW":[63],"of":[64,83],"power":[65],"consumption.":[66],"Long-term,":[67],"multi-stage":[68],"synaptic":[69],"memory":[70],"contains":[71],"more":[72],"information":[73],"a":[75,79],"longer":[76],"time":[77],"in":[78],"single":[80],"synapse.":[81],"Comparison":[82],"proposed":[85],"PSNN":[86],"recent":[88],"hardware":[89],"networks":[91],"also":[93],"provided.":[94]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
