{"id":"https://openalex.org/W4385218315","doi":"https://doi.org/10.23919/vlsitechnologyandcir57934.2023.10185410","title":"ANP-G: A 28nm 1.04pJ/SOP Sub-mm2 Spiking and Back-propagation Hybrid Neural Network Asynchronous Olfactory Processor Enabling Few-shot Class-incremental On-chip Learning","display_name":"ANP-G: A 28nm 1.04pJ/SOP Sub-mm2 Spiking and Back-propagation Hybrid Neural Network Asynchronous Olfactory Processor Enabling Few-shot Class-incremental On-chip Learning","publication_year":2023,"publication_date":"2023-06-11","ids":{"openalex":"https://openalex.org/W4385218315","doi":"https://doi.org/10.23919/vlsitechnologyandcir57934.2023.10185410"},"language":"en","primary_location":{"id":"doi:10.23919/vlsitechnologyandcir57934.2023.10185410","is_oa":false,"landing_page_url":"https://doi.org/10.23919/vlsitechnologyandcir57934.2023.10185410","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)","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/A5088276807","display_name":"Dexuan Huo","orcid":"https://orcid.org/0000-0002-0452-3998"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dexuan Huo","raw_affiliation_strings":["Tsinghua University,Beijing,China","Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100624320","display_name":"Jilin Zhang","orcid":"https://orcid.org/0000-0002-0423-9356"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jilin Zhang","raw_affiliation_strings":["Tsinghua University,Beijing,China","Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102994315","display_name":"Xinyu Dai","orcid":"https://orcid.org/0000-0002-4139-7337"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Dai","raw_affiliation_strings":["Tsinghua University,Beijing,China","Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100409920","display_name":"Jian Zhang","orcid":"https://orcid.org/0000-0002-0755-6779"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Zhang","raw_affiliation_strings":["Tsinghua University,Beijing,China","Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074747392","display_name":"Chunqi Qian","orcid":"https://orcid.org/0000-0003-4528-4572"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunqi Qian","raw_affiliation_strings":["Tsinghua University,Beijing,China","Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","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":["National Tsing Hua University,Hsinchu,Taiwan","National Tsing Hua University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100420459","display_name":"Hong Chen","orcid":"https://orcid.org/0000-0003-0774-1410"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Chen","raw_affiliation_strings":["Tsinghua University,Beijing,China","Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5088276807"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.3388,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.80507478,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9969000220298767,"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":0.9969000220298767,"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":0.9940999746322632,"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":0.9817000031471252,"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/asynchronous-communication","display_name":"Asynchronous communication","score":0.791480541229248},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6681141257286072},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5801669359207153},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5760997533798218},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.5389941334724426},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.5363197922706604},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.5224917531013489},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4434584975242615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43432751297950745},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.43102583289146423},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20040848851203918},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.11955368518829346},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11449655890464783}],"concepts":[{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.791480541229248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6681141257286072},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5801669359207153},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5760997533798218},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.5389941334724426},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.5363197922706604},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.5224917531013489},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4434584975242615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43432751297950745},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.43102583289146423},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20040848851203918},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.11955368518829346},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11449655890464783},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/vlsitechnologyandcir57934.2023.10185410","is_oa":false,"landing_page_url":"https://doi.org/10.23919/vlsitechnologyandcir57934.2023.10185410","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8899999856948853,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4214877189","https://openalex.org/W2074502265","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2334685461","https://openalex.org/W2116677773","https://openalex.org/W2366718574","https://openalex.org/W2359774528","https://openalex.org/W4298312966","https://openalex.org/W2728912566"],"abstract_inverted_index":{"This":[0,45],"paper":[1],"presents":[2],"a":[3],"28nm":[4],"1.04pJ/SOP":[5],"sub-mm":[6],"<sup":[7],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[8],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[9],"spiking":[10],"and":[11,40,49,59],"back-propagation":[12],"hybrid":[13],"neural":[14],"network":[15],"asynchronous":[16],"olfactory":[17],"processor":[18,46],"enabling":[19],"few-shot":[20],"class-incremental":[21],"on-chip":[22],"learning":[23,43],"for":[24],"the":[25,55],"first":[26],"time,":[27],"showing":[28],"<33.27\u03bcW":[29],"training":[30],"power":[31],"budget":[32],"at":[33],"0.55V":[34],"with":[35],"gas":[36,41,57],"recognition,":[37],"concentration":[38],"estimation,":[39],"incremental":[42],"tasks.":[44],"achieves":[47],"110.62\u00d7":[48],"4.09\u00d7":[50],"energy":[51],"saving":[52],"respectively":[53],"over":[54],"state-of-the-art":[56],"recognition":[58],"SNN":[60],"chips.":[61]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5}],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2025-10-10T00:00:00"}