{"id":"https://openalex.org/W3161146689","doi":"https://doi.org/10.1109/isqed51717.2021.9424267","title":"Low-power Analog and Mixed-signal IC Design of Multiplexing Neural Encoder in Neuromorphic Computing","display_name":"Low-power Analog and Mixed-signal IC Design of Multiplexing Neural Encoder in Neuromorphic Computing","publication_year":2021,"publication_date":"2021-04-07","ids":{"openalex":"https://openalex.org/W3161146689","doi":"https://doi.org/10.1109/isqed51717.2021.9424267","mag":"3161146689"},"language":"en","primary_location":{"id":"doi:10.1109/isqed51717.2021.9424267","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isqed51717.2021.9424267","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 22nd International Symposium on Quality Electronic Design (ISQED)","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/A5079345564","display_name":"Honghao Zheng","orcid":"https://orcid.org/0000-0002-2408-5710"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Honghao Zheng","raw_affiliation_strings":["Virginia Tech, Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077195982","display_name":"Nima Mohammadi","orcid":"https://orcid.org/0000-0002-3251-1951"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nima Mohammadi","raw_affiliation_strings":["Virginia Tech, Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082108426","display_name":"Kangjun Bai","orcid":"https://orcid.org/0000-0003-4437-0006"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kangjun Bai","raw_affiliation_strings":["Virginia Tech, Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018632091","display_name":"Yang Yi","orcid":"https://orcid.org/0000-0002-1354-0204"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Yi","raw_affiliation_strings":["Virginia Tech, Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079345564"],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":0.5014,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.63067565,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"154","last_page":"159"},"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9995999932289124,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9986000061035156,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7906144857406616},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.7895286083221436},{"id":"https://openalex.org/keywords/multiplexing","display_name":"Multiplexing","score":0.7739524841308594},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6568259596824646},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6318902969360352},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4251723289489746},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.396634042263031},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3919992446899414},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2730317711830139},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18003147840499878},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14316034317016602},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10920393466949463}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7906144857406616},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.7895286083221436},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.7739524841308594},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6568259596824646},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6318902969360352},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4251723289489746},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.396634042263031},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3919992446899414},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2730317711830139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18003147840499878},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14316034317016602},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10920393466949463},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isqed51717.2021.9424267","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isqed51717.2021.9424267","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 22nd International Symposium on Quality Electronic Design (ISQED)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W12277440","https://openalex.org/W190453290","https://openalex.org/W1978306818","https://openalex.org/W1985489865","https://openalex.org/W2000159440","https://openalex.org/W2061056596","https://openalex.org/W2092359409","https://openalex.org/W2342641844","https://openalex.org/W2515215277","https://openalex.org/W2535636396","https://openalex.org/W2921042813","https://openalex.org/W2972441480","https://openalex.org/W2972526195","https://openalex.org/W2979610412","https://openalex.org/W2998689804","https://openalex.org/W6600493916","https://openalex.org/W6607761541","https://openalex.org/W6629135394","https://openalex.org/W6725832498","https://openalex.org/W6768060164","https://openalex.org/W6990847847"],"related_works":["https://openalex.org/W2986579802","https://openalex.org/W3108691306","https://openalex.org/W4389237622","https://openalex.org/W2166309310","https://openalex.org/W4385753159","https://openalex.org/W4283822356","https://openalex.org/W1950940422","https://openalex.org/W2129146436","https://openalex.org/W2032507829","https://openalex.org/W2147282173"],"abstract_inverted_index":{"The":[0,199,210,244],"research":[1],"on":[2,190],"computing":[3],"clusters":[4],"comprising":[5],"neuromorphic":[6],"systems":[7],"has":[8,70],"drawn":[9],"the":[10,16,27,38,56,79,96,100,107,131,134,151,169,174,195,208,222,228,233,248,254,263,268],"interest":[11],"of":[12,34,40,67,98,123,130,143,157,207,224,232,247,256,272],"many":[13],"researchers":[14],"in":[15,55],"field.":[17],"Neural":[18],"encoding":[19,50,90,153,242],"is":[20,29,137,202,214,227,237,250],"a":[21,32,46,119,155,260],"crucial":[22],"component":[23],"that":[24,236],"determines":[25],"how":[26],"information":[28],"conveyed":[30],"through":[31],"train":[33],"spikes,":[35],"greatly":[36],"impacting":[37],"mode":[39],"operations'":[41],"and":[42,63,74,187,258],"systems'":[43],"performance":[44,101],"to":[45,81,139,177,193,221,253],"large":[47],"extent.":[48],"Numerous":[49],"schemes":[51,69,94],"have":[52],"been":[53],"proposed":[54,152],"literature,":[57],"including":[58],"latency":[59,178],"encoding,":[60,62,133],"ISI":[61],"phase":[64],"encoding.":[65],"Each":[66],"these":[68,182],"its":[71],"own":[72],"benefits":[73],"shortcomings":[75],"which":[76,161],"brings":[77],"up":[78],"idea":[80],"see":[82],"if":[83],"they":[84],"can":[85,162],"complement":[86],"each":[87,191],"other.":[88],"Multiplexing":[89],"combines":[91],"two":[92,240],"different":[93,241],"with":[95,216],"aim":[97],"enhancing":[99],"via":[102],"conveying":[103],"more":[104,110],"information,":[105],"making":[106],"encoded":[108],"spikes":[109],"robust":[111],"against":[112],"noise.":[113],"In":[114,150],"this":[115],"paper,":[116],"we":[117],"introduce":[118],"mixed-signal":[120],"IC":[121,230],"design":[122,231],"multiplexing":[124,132,234],"latency-phase":[125,235],"encoder.":[126,209],"A":[127],"key":[128],"principle":[129],"gamma":[135],"alignment,":[136],"employed":[138],"achieve":[140],"enhanced":[141],"functionality":[142],"spiking":[144,159],"neurons":[145],"supported":[146],"by":[147],"biological":[148],"research.":[149],"scheme,":[154],"set":[156],"predetermined":[158],"neurons,":[160,257],"be":[163],"perceived":[164],"as":[165],"dimensionality":[166],"reduction":[167],"over":[168],"grouped":[170],"higher-dimensional":[171],"stimuli,":[172],"maps":[173],"input":[175],"currents":[176],"spike":[179,183,197],"trains.":[180],"Consequently,":[181],"trains":[184],"are":[185],"aligned":[186],"then":[188],"superimposed":[189],"other":[192],"form":[194],"resulting":[196],"train.":[198],"simulation":[200,265],"result":[201,266],"carefully":[203],"inspected":[204],"for":[205,259],"verification":[206],"introduced":[211],"power-efficient":[212],"circuit":[213,269],"designed":[215],"180nm":[217],"CMOS":[218],"technology":[219],"and,":[220],"best":[223],"our":[225],"knowledge,":[226],"first":[229],"built":[238],"upon":[239],"schemes.":[243],"power":[245],"consumption":[246],"encoder":[249],"generally":[251],"proportional":[252],"number":[255],"4-neuron":[261],"structure,":[262],"layout-level":[264],"shows":[267],"consumes":[270],"10mW":[271],"power.":[273]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}