{"id":"https://openalex.org/W1669276382","doi":"https://doi.org/10.1109/islped.2015.7273495","title":"A power-aware digital feedforward neural network platform with backpropagation driven approximate synapses","display_name":"A power-aware digital feedforward neural network platform with backpropagation driven approximate synapses","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W1669276382","doi":"https://doi.org/10.1109/islped.2015.7273495","mag":"1669276382"},"language":"en","primary_location":{"id":"doi:10.1109/islped.2015.7273495","is_oa":false,"landing_page_url":"https://doi.org/10.1109/islped.2015.7273495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 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/A5079872127","display_name":"Jaeha Kung","orcid":"https://orcid.org/0000-0001-6151-8602"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jaeha Kung","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Department of Electrical and Computer Engineering, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, 30332, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, 30332, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041847927","display_name":"Duck-Hwan Kim","orcid":"https://orcid.org/0000-0002-6494-2182"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Duckhwan Kim","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Department of Electrical and Computer Engineering, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, 30332, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, 30332, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009591041","display_name":"Saibal Mukhopadhyay","orcid":"https://orcid.org/0000-0002-8894-3390"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saibal Mukhopadhyay","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Department of Electrical and Computer Engineering, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, 30332, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, 30332, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":5.1449,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.96496918,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"85","last_page":"90"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9998000264167786,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/backpropagation","display_name":"Backpropagation","score":0.8961600065231323},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7409122586250305},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7134463787078857},{"id":"https://openalex.org/keywords/feedforward-neural-network","display_name":"Feedforward neural network","score":0.5486732721328735},{"id":"https://openalex.org/keywords/rprop","display_name":"Rprop","score":0.45705530047416687},{"id":"https://openalex.org/keywords/feed-forward","display_name":"Feed forward","score":0.45279937982559204},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.36895751953125},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.36754271388053894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35650330781936646},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3314816653728485},{"id":"https://openalex.org/keywords/types-of-artificial-neural-networks","display_name":"Types of artificial neural networks","score":0.16502398252487183},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15785855054855347},{"id":"https://openalex.org/keywords/control-engineering","display_name":"Control engineering","score":0.12721878290176392}],"concepts":[{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.8961600065231323},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7409122586250305},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7134463787078857},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.5486732721328735},{"id":"https://openalex.org/C98359873","wikidata":"https://www.wikidata.org/wiki/Q1320470","display_name":"Rprop","level":5,"score":0.45705530047416687},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.45279937982559204},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.36895751953125},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.36754271388053894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35650330781936646},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3314816653728485},{"id":"https://openalex.org/C177973122","wikidata":"https://www.wikidata.org/wiki/Q7860946","display_name":"Types of artificial neural networks","level":4,"score":0.16502398252487183},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15785855054855347},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.12721878290176392}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/islped.2015.7273495","is_oa":false,"landing_page_url":"https://doi.org/10.1109/islped.2015.7273495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 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":0.8700000047683716,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1968268201","https://openalex.org/W1998917233","https://openalex.org/W2044535169","https://openalex.org/W2047244809","https://openalex.org/W2051831389","https://openalex.org/W2063906779","https://openalex.org/W2100495367","https://openalex.org/W2101048693","https://openalex.org/W2114837206","https://openalex.org/W2163605009","https://openalex.org/W4246795461","https://openalex.org/W6661509636","https://openalex.org/W6677490153","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W1604847762","https://openalex.org/W2086999410","https://openalex.org/W2154381864","https://openalex.org/W2160276773","https://openalex.org/W97768505","https://openalex.org/W2023448200","https://openalex.org/W2144079614","https://openalex.org/W2019516876","https://openalex.org/W1824158299","https://openalex.org/W2391384657"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,22,29,37,62,87,105],"power-aware":[4],"digital":[5],"feedforward":[6],"neural":[7,38],"network":[8],"platform":[9],"that":[10],"utilizes":[11],"the":[12,25,52,72,91],"backpropagation":[13,53],"algorithm":[14],"during":[15],"training":[16],"to":[17,86],"enable":[18],"energy-quality":[19],"trade-off.":[20],"Given":[21],"quality":[23],"constraint,":[24],"proposed":[26,92],"approach":[27,41,93],"identifies":[28],"set":[30],"of":[31],"synaptic":[32],"weights":[33],"for":[34,55],"approximation":[35],"in":[36,71,81,104],"network.":[39],"The":[40,57,78],"selects":[42],"synapses":[43],"with":[44,99],"small":[45],"impact":[46],"on":[47],"output":[48],"error,":[49],"estimated":[50],"by":[51,61,97],"algorithm,":[54],"approximation.":[56],"approximations":[58],"are":[59],"achieved":[60],"coupled":[63],"software":[64],"(reduced":[65],"bit-width)":[66],"and":[67],"hardware":[68],"(approximate":[69],"multiplication":[70],"processing":[73],"engine)":[74],"based":[75],"design":[76,80],"approaches.":[77],"full-chip":[79],"130nm":[82],"CMOS":[83],"shows,":[84],"compared":[85],"baseline":[88],"accurate":[89],"design,":[90],"reduces":[94],"system":[95],"power":[96],"~38%":[98],"0.4%":[100],"lower":[101],"recognition":[102],"accuracy":[103],"classification":[106],"problem.":[107]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":6}],"updated_date":"2026-08-02T14:50:37.381335","created_date":"2025-10-10T00:00:00"}