{"id":"https://openalex.org/W2971541781","doi":"https://doi.org/10.1109/islped.2019.8824938","title":"An Energy-efficient On-chip Learning Architecture for STDP based Sparse Coding","display_name":"An Energy-efficient On-chip Learning Architecture for STDP based Sparse Coding","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2971541781","doi":"https://doi.org/10.1109/islped.2019.8824938","mag":"2971541781"},"language":"en","primary_location":{"id":"doi:10.1109/islped.2019.8824938","is_oa":false,"landing_page_url":"https://doi.org/10.1109/islped.2019.8824938","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5084915481","display_name":"Heetak Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Heetak Kim","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seongbuk-Gu, Seoul"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seongbuk-Gu, Seoul","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041682981","display_name":"Hoyoung Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hoyoung Tang","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seongbuk-Gu, Seoul"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seongbuk-Gu, Seoul","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101839916","display_name":"Jongsun Park","orcid":"https://orcid.org/0000-0003-3251-0024"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jongsun Park","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seongbuk-Gu, Seoul"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seongbuk-Gu, Seoul","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":0.3982,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.4907859,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"521","issue":null,"first_page":"1","last_page":"6"},"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular 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/T10581","display_name":"Neural dynamics and brain function","score":0.9991999864578247,"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":0.8109014630317688},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.7207634449005127},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5811640620231628},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5473338961601257},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.5439079999923706},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4402739703655243},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4206942021846771},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.4150164723396301},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.41388681530952454},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4131298065185547},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.3921095132827759},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3153899312019348},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2936784029006958},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2630220651626587},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1993815004825592},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.114704430103302},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08665376901626587}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8109014630317688},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.7207634449005127},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5811640620231628},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5473338961601257},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.5439079999923706},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4402739703655243},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4206942021846771},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.4150164723396301},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.41388681530952454},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4131298065185547},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3921095132827759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3153899312019348},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2936784029006958},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2630220651626587},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1993815004825592},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.114704430103302},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08665376901626587},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/islped.2019.8824938","is_oa":false,"landing_page_url":"https://doi.org/10.1109/islped.2019.8824938","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8999999761581421,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W101771737","https://openalex.org/W2006370340","https://openalex.org/W2038511109","https://openalex.org/W2093618981","https://openalex.org/W2112796928","https://openalex.org/W2113606819","https://openalex.org/W2131763976","https://openalex.org/W2133128597","https://openalex.org/W2145889472","https://openalex.org/W2147101007","https://openalex.org/W2202505358","https://openalex.org/W2528596247","https://openalex.org/W2635692202","https://openalex.org/W2783873980","https://openalex.org/W2898990213","https://openalex.org/W2919115771","https://openalex.org/W6676903177"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2950475743","https://openalex.org/W2886711096","https://openalex.org/W2750384547","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W4389249638","https://openalex.org/W2733410219","https://openalex.org/W4390060806","https://openalex.org/W3013241373"],"abstract_inverted_index":{"Two":[0],"main":[1],"bottlenecks":[2],"encountered":[3],"when":[4],"implementing":[5],"energy-efficient":[6,36],"spike-timing-dependent":[7],"plasticity":[8],"(STDP)":[9],"based":[10,38,46,60,69,99],"sparse":[11,39,100],"coding,":[12],"are":[13,76],"the":[14,26,54,62,82,94,97,110,139,144,148],"complex":[15,55],"computation":[16,117],"of":[17,64,96,142,150,156],"winner-take-all":[18],"(WTA)":[19],"operation":[20,57],"and":[21,73,92,132,152,158],"repetitive":[22],"neuronal":[23],"operations":[24],"in":[25,71],"time":[27],"domain":[28,75],"processing.":[29],"In":[30,138],"this":[31],"paper,":[32],"we":[33],"present":[34],"an":[35],"STDP":[37,98],"coding":[40,101],"processor.":[41],"The":[42],"low-cost":[43],"hardware":[44,95,146],"is":[45,58],"on":[47,61],"algorithmic":[48,87,123],"reduction":[49],"techniques":[50],"as":[51],"following:":[52],"First,":[53],"WTA":[56],"simplified":[59],"prediction":[63],"spike":[65],"emitting":[66],"neurons.":[67],"Sparsity":[68],"approximation":[70],"spatial":[72],"temporal":[74],"also":[77],"efficiently":[78],"exploited":[79],"to":[80,120],"remove":[81],"redundant":[83],"neurons":[84],"with":[85,122,154],"negligible":[86],"accuracy":[88],"loss.":[89],"We":[90],"designed":[91],"implemented":[93],"using":[102],"65nm":[103],"CMOS":[104],"process.":[105],"By":[106],"exploiting":[107],"input":[108],"sparsity,":[109],"proposed":[111],"architecture":[112],"can":[113],"dynamically":[114],"trade":[115],"off":[116],"energy":[118],"(up":[119],"74%)":[121],"quality":[124,130,135],"for":[125],"Natural":[126],"image":[127],"(maximum":[128],"3.55%":[129],"loss)":[131,136],"MNIST":[133],"(no":[134],"applications.":[137],"inference":[140],"mode":[141],"operations,":[143],"SNN":[145],"achieves":[147],"throughput":[149],"374Mpixels/s":[151],"840.2GSOP/s":[153],"energy-efficiency":[155],"781.52pJ/pixel":[157],"0.35pJ/SOP.":[159]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}