{"id":"https://openalex.org/W4324291243","doi":"https://doi.org/10.1109/tcsi.2023.3253705","title":"S-QRD-ELM: Scalable QR-Decomposition-Based Extreme Learning Machine Engine Supporting Online Class-Incremental Learning for ECG-Based User Identification","display_name":"S-QRD-ELM: Scalable QR-Decomposition-Based Extreme Learning Machine Engine Supporting Online Class-Incremental Learning for ECG-Based User Identification","publication_year":2023,"publication_date":"2023-03-14","ids":{"openalex":"https://openalex.org/W4324291243","doi":"https://doi.org/10.1109/tcsi.2023.3253705"},"language":"en","primary_location":{"id":"doi:10.1109/tcsi.2023.3253705","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsi.2023.3253705","pdf_url":null,"source":{"id":"https://openalex.org/S116977442","display_name":"IEEE Transactions on Circuits and Systems I Regular Papers","issn_l":"1549-8328","issn":["1549-8328","1558-0806"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems I: Regular Papers","raw_type":"journal-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/A5060083525","display_name":"Yi-Ta Chen","orcid":"https://orcid.org/0000-0003-1724-0206"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yi-Ta Chen","raw_affiliation_strings":["Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan"],"raw_orcid":"https://orcid.org/0000-0003-1724-0206","affiliations":[{"raw_affiliation_string":"Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069905671","display_name":"Yu-Chuan Chuang","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Chuan Chuang","raw_affiliation_strings":["Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan"],"raw_orcid":"https://orcid.org/0000-0001-7940-9033","affiliations":[{"raw_affiliation_string":"Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057700442","display_name":"Li\u2010Sheng Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148979","display_name":"MediaTek (Taiwan)","ror":"https://ror.org/05g9jck81","country_code":"TW","type":"company","lineage":["https://openalex.org/I4210148979"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Li-Sheng Chang","raw_affiliation_strings":["MediaTek Inc., Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MediaTek Inc., Hsinchu, Taiwan","institution_ids":["https://openalex.org/I4210148979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109465340","display_name":"An-Yeu Wu","orcid":"https://orcid.org/0000-0003-4731-8633"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"An-Yeu Wu","raw_affiliation_strings":["Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan"],"raw_orcid":"https://orcid.org/0000-0003-4731-8633","affiliations":[{"raw_affiliation_string":"Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7824,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76232283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"70","issue":"6","first_page":"2342","last_page":"2355"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":1.0,"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/T12676","display_name":"Machine Learning and ELM","score":1.0,"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":0.9861999750137329,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9789000153541565,"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/computer-science","display_name":"Computer science","score":0.6422922611236572},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.5727701187133789},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5474822521209717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5326615571975708},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4876762628555298},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.46819719672203064},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4383479654788971},{"id":"https://openalex.org/keywords/qr-decomposition","display_name":"QR decomposition","score":0.42583465576171875},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3942790925502777},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.18518459796905518},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10669019818305969}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6422922611236572},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.5727701187133789},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5474822521209717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5326615571975708},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4876762628555298},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.46819719672203064},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4383479654788971},{"id":"https://openalex.org/C188060507","wikidata":"https://www.wikidata.org/wiki/Q653242","display_name":"QR decomposition","level":3,"score":0.42583465576171875},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3942790925502777},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.18518459796905518},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10669019818305969},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"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},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsi.2023.3253705","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsi.2023.3253705","pdf_url":null,"source":{"id":"https://openalex.org/S116977442","display_name":"IEEE Transactions on Circuits and Systems I Regular Papers","issn_l":"1549-8328","issn":["1549-8328","1558-0806"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems I: Regular Papers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G384490329","display_name":"Multi-Modal Affective Computing Based on Imaging and Environmental Sensors (Phase Ii)( II )","funder_award_id":"MOST109-2622-8002-012-TA","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G4808801089","display_name":"Developments of Enabling Devices and Intelligent Architectures for High-Density and High-Performance Semiconductors( II )","funder_award_id":"MOST111-2218-E002-018-MBK","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G6109489112","display_name":"Developments of Enabling Devices and Intelligent Architectures for High-density and High-performance Semiconductors( I )","funder_award_id":"MOST110-2218-E002-034-MBK","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G6935793436","display_name":"Multi-Modal Affective Computing Circuits and System for Intelligent Fog-Based Internet of Things","funder_award_id":"MOST106-2221-E002-205-MY3","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W26658632","https://openalex.org/W31566076","https://openalex.org/W2011961109","https://openalex.org/W2111072639","https://openalex.org/W2138061685","https://openalex.org/W2150633168","https://openalex.org/W2162273778","https://openalex.org/W2162800060","https://openalex.org/W2473930607","https://openalex.org/W2560647685","https://openalex.org/W2782009593","https://openalex.org/W2794557162","https://openalex.org/W2898485213","https://openalex.org/W2911149048","https://openalex.org/W2939137134","https://openalex.org/W2945997721","https://openalex.org/W2963347423","https://openalex.org/W2964189064","https://openalex.org/W3081320461","https://openalex.org/W3122976726","https://openalex.org/W3125116114","https://openalex.org/W3158528914","https://openalex.org/W4226236362","https://openalex.org/W4285171379","https://openalex.org/W4304149893","https://openalex.org/W6601248315","https://openalex.org/W6795846790"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W31566076","https://openalex.org/W4297902562","https://openalex.org/W2741186499","https://openalex.org/W2804652951","https://openalex.org/W2556335056","https://openalex.org/W2002678693","https://openalex.org/W1584764049","https://openalex.org/W2743832667","https://openalex.org/W4206282396"],"abstract_inverted_index":{"User":[0],"identification":[1,18,48],"enables":[2],"secure":[3],"access":[4],"to":[5,22,29,51,118,153,245],"data":[6],"and":[7,27,91,111,158,192,218],"machines":[8],"in":[9,128,202],"smart":[10],"factories.":[11],"Compared":[12],"with":[13,133,138,178,206],"other":[14,35],"modalities,":[15],"ECG-based":[16,46,96,252],"user":[17,47,97,253],"is":[19,151,200,241],"rising":[20],"due":[21],"its":[23],"intrinsic":[24],"liveness":[25],"proof":[26],"invulnerability":[28],"spoofing":[30],"without":[31],"contact.":[32],"On":[33],"the":[34,43,45,56,100,105,119,129,134,142,156,163,168,172,179,190,195,227,230,235,242,247],"hand,":[36],"as":[37,65],"new":[38,57],"employees":[39],"are":[40],"registered":[41],"at":[42],"factory,":[44],"system":[49],"needs":[50],"be":[52,63],"updated":[53],"based":[54],"on":[55],"coming":[58],"data.":[59],"This":[60,121,198],"scenario":[61,131],"can":[62,89],"defined":[64],"an":[66],"online":[67],"class-incremental":[68],"learning":[69,84,219],"(O-CIL)":[70],"problem.":[71],"By":[72],"exploiting":[73],"hardware-software":[74],"co-":[75],"design,":[76],"this":[77],"work":[78],"presents":[79],"a":[80,145],"Scalable":[81],"QR-decomposition-based":[82],"extreme":[83],"machine":[85],"(S-QRD-ELM)":[86],"engine":[87,199,240],"that":[88],"effectively":[90],"efficiently":[92,154],"support":[93],"O-CIL":[94,130,250],"for":[95,251],"identification.":[98,254],"At":[99,141],"software":[101],"level,":[102,144],"we":[103],"apply":[104],"concept":[106],"of":[107,167,189,194,232,249],"\u201cthe":[108],"others\u201d":[109],"class":[110],"inversion-free":[112],"QR-decomposition":[113],"(QRD)":[114],"recursive":[115],"least":[116],"squares":[117],"S-QRD-ELM.":[120],"makes":[122],"S-QRD-ELM":[123,239],"achieve":[124],"79.7%":[125],"higher":[126],"accuracy":[127],"compared":[132],"neural":[135],"network":[136],"trained":[137],"back-propagation":[139],"(BP-NN).":[140],"hardware":[143],"one-dimensional":[146],"diagonally-mapped":[147],"linear":[148],"array":[149],"(1D-DMLA)":[150],"proposed":[152,236],"compute":[155],"QRD":[157],"back-substitution":[159],"(BS)":[160],"operations":[161],"inside":[162],"S-QRD-ELM,":[164],"reducing":[165],"98.5%":[166],"silicon":[169],"area.":[170,210],"Moreover,":[171],"integrated":[173],"processing":[174],"element":[175],"(PE)":[176],"design":[177],"unified":[180],"COordinate":[181],"Rotation":[182],"DIgital":[183],"Computer":[184],"(u-CORDIC)":[185],"further":[186],"reduces":[187],"15.3%":[188],"area":[191],"22.4%":[193],"power":[196],"consumption.":[197],"fabricated":[201],"40nm":[203],"CMOS":[204],"technology":[205],"a$1.33\\times":[207],"1.33$mm2":[208],"die":[209],"The":[211],"chip":[212,244],"achieves$0.02\\mu":[213],"\\text{J}$/sample":[214,216],"and$2.47\\mu":[215],"inferencing":[217],"energy":[220],"efficiency,":[221],"respectively,":[222],"which":[223],"is$6.4\\times":[224],"$and$28.5\\times":[225],"$than":[226],"state-of-the-art.":[228],"To":[229],"best":[231],"our":[233],"knowledge,":[234],"highly":[237],"energy-efficient":[238],"first":[243],"meet":[246],"requirements":[248]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}