{"id":"https://openalex.org/W4407404472","doi":"https://doi.org/10.1109/tcad.2025.3541565","title":"Online Training and Inference System on Edge FPGA Using Delayed Feedback Reservoir","display_name":"Online Training and Inference System on Edge FPGA Using Delayed Feedback Reservoir","publication_year":2025,"publication_date":"2025-02-12","ids":{"openalex":"https://openalex.org/W4407404472","doi":"https://doi.org/10.1109/tcad.2025.3541565"},"language":"en","primary_location":{"id":"doi:10.1109/tcad.2025.3541565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcad.2025.3541565","pdf_url":null,"source":{"id":"https://openalex.org/S100835903","display_name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","issn_l":"0278-0070","issn":["0278-0070","1937-4151"],"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 Computer-Aided Design of Integrated Circuits and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2504.11970","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052196231","display_name":"Sosei Ikeda","orcid":"https://orcid.org/0000-0002-5046-7405"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]},{"id":"https://openalex.org/I39012071","display_name":"Kyoto College of Graduate Studies for Informatics","ror":"https://ror.org/05mzj8a56","country_code":"JP","type":"education","lineage":["https://openalex.org/I39012071"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sosei Ikeda","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0002-5046-7405","affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I39012071","https://openalex.org/I22299242"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102716651","display_name":"Hiromitsu Awano","orcid":"https://orcid.org/0000-0002-3674-4584"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]},{"id":"https://openalex.org/I39012071","display_name":"Kyoto College of Graduate Studies for Informatics","ror":"https://ror.org/05mzj8a56","country_code":"JP","type":"education","lineage":["https://openalex.org/I39012071"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiromitsu Awano","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0002-3674-4584","affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I39012071","https://openalex.org/I22299242"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017861176","display_name":"Takashi Sat\u014d","orcid":"https://orcid.org/0000-0002-1577-8259"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]},{"id":"https://openalex.org/I39012071","display_name":"Kyoto College of Graduate Studies for Informatics","ror":"https://ror.org/05mzj8a56","country_code":"JP","type":"education","lineage":["https://openalex.org/I39012071"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takashi Sato","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0002-1577-8259","affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I39012071","https://openalex.org/I22299242"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00895072,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"44","issue":"9","first_page":"3323","last_page":"3335"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9406999945640564,"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":0.9406999945640564,"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/T10320","display_name":"Neural Networks and Applications","score":0.9228000044822693,"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":0.9196000099182129,"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/training","display_name":"Training (meteorology)","score":0.8170896768569946},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7344702482223511},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6863483190536499},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.6582252979278564},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6032530069351196},{"id":"https://openalex.org/keywords/training-system","display_name":"Training system","score":0.4842948317527771},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43886247277259827},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.42163392901420593},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41224175691604614},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.29218965768814087},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07951465249061584}],"concepts":[{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.8170896768569946},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7344702482223511},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6863483190536499},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.6582252979278564},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6032530069351196},{"id":"https://openalex.org/C2776857766","wikidata":"https://www.wikidata.org/wiki/Q7832987","display_name":"Training system","level":2,"score":0.4842948317527771},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43886247277259827},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.42163392901420593},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41224175691604614},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.29218965768814087},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07951465249061584},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcad.2025.3541565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcad.2025.3541565","pdf_url":null,"source":{"id":"https://openalex.org/S100835903","display_name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","issn_l":"0278-0070","issn":["0278-0070","1937-4151"],"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 Computer-Aided Design of Integrated Circuits and Systems","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2504.11970","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2504.11970","pdf_url":"https://arxiv.org/pdf/2504.11970","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2504.11970","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2504.11970","pdf_url":"https://arxiv.org/pdf/2504.11970","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2734826064","display_name":null,"funder_award_id":"23H03362","funder_id":"https://openalex.org/F4320320212","funder_display_name":"Japan Society for the Promotion of Science London"},{"id":"https://openalex.org/G733452386","display_name":null,"funder_award_id":"23H03362","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7879946292","display_name":null,"funder_award_id":"23K18462","funder_id":"https://openalex.org/F4320320212","funder_display_name":"Japan Society for the Promotion of Science London"},{"id":"https://openalex.org/G8282729643","display_name":null,"funder_award_id":"23K28052","funder_id":"https://openalex.org/F4320320212","funder_display_name":"Japan Society for the Promotion of Science London"}],"funders":[{"id":"https://openalex.org/F4320320212","display_name":"Japan Society for the Promotion of Science London","ror":"https://ror.org/02m7axw05"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4407404472.pdf","grobid_xml":"https://content.openalex.org/works/W4407404472.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W119403003","https://openalex.org/W1545528966","https://openalex.org/W1646015841","https://openalex.org/W1970861901","https://openalex.org/W1971066582","https://openalex.org/W1977664984","https://openalex.org/W1992468081","https://openalex.org/W2022248835","https://openalex.org/W2034996255","https://openalex.org/W2046458632","https://openalex.org/W2094631910","https://openalex.org/W2171865010","https://openalex.org/W2551393996","https://openalex.org/W2585354796","https://openalex.org/W2598525681","https://openalex.org/W2887258823","https://openalex.org/W2892035503","https://openalex.org/W2963661130","https://openalex.org/W3021951958","https://openalex.org/W3038427506","https://openalex.org/W3200482402","https://openalex.org/W4200033355","https://openalex.org/W4292336553","https://openalex.org/W4312220016","https://openalex.org/W4386574781"],"related_works":["https://openalex.org/W2111241003","https://openalex.org/W2355315220","https://openalex.org/W4200391368","https://openalex.org/W2210979487","https://openalex.org/W2316202402","https://openalex.org/W2074043759","https://openalex.org/W2082487009","https://openalex.org/W2373535795","https://openalex.org/W3103262449","https://openalex.org/W2787763930"],"abstract_inverted_index":{"A":[0,73],"delayed":[1],"feedback":[2],"reservoir":[3,8,60],"(DFR)":[4],"is":[5,30,46,77,97,118],"a":[6,51,69],"hardware-friendly":[7],"computing":[9],"system.":[10],"Implementing":[11],"DFRs":[12],"in":[13],"embedded":[14],"hardware":[15],"requires":[16],"efficient":[17],"online":[18,133],"training.":[19],"However,":[20],"two":[21],"main":[22],"challenges":[23],"prevent":[24],"this:":[25],"1)":[26],"hyperparameter":[27],"selection,":[28],"which":[29,45],"typically":[31],"done":[32],"by":[33,67,147,153],"offline":[34],"grid":[35,102],"search,":[36],"and":[37,53,64,136,150],"2)":[38],"training":[39,135],"of":[40,87,131,139],"the":[41,59,85,88,111,129,161],"output":[42,112],"linear":[43],"layer,":[44],"memory-intensive.":[47],"This":[48],"article":[49],"introduces":[50],"fast":[52],"accurate":[54],"parameter":[55],"optimization":[56],"method":[57],"for":[58,110],"layer":[61,113],"utilizing":[62],"backpropagation":[63,75],"gradient":[65],"descent":[66],"adopting":[68],"modular":[70],"DFR":[71,140],"model.":[72],"truncated":[74],"strategy":[76],"proposed":[78],"to":[79,101,123,157],"reduce":[80],"memory":[81,121],"consumption":[82,152],"associated":[83],"with":[84],"expansion":[86],"recursive":[89],"structure":[90],"while":[91],"maintaining":[92],"accuracy.":[93],"The":[94],"computation":[95,145],"time":[96,146],"significantly":[98],"reduced":[99],"compared":[100,156],"search.":[103],"In":[104],"addition,":[105],"an":[106,132,142],"in-place":[107],"Ridge":[108],"regression":[109],"via":[114],"1-D":[115],"Cholesky":[116],"decomposition":[117],"presented,":[119],"reducing":[120,144],"usage":[122],"be":[124],"1/4.":[125],"These":[126],"methods":[127],"enable":[128],"realization":[130],"edge":[134],"inference":[137],"system":[138],"on":[141,160],"FPGA,":[143],"about":[148,154],"1/13":[149],"power":[151],"1/27":[155],"software":[158],"implementation":[159],"same":[162],"board.":[163]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
