{"id":"https://openalex.org/W2167656351","doi":"https://doi.org/10.1109/ijcnn.2004.1381065","title":"Training fast mixed-signal neural networks for data classification","display_name":"Training fast mixed-signal neural networks for data classification","publication_year":2005,"publication_date":"2005-02-28","ids":{"openalex":"https://openalex.org/W2167656351","doi":"https://doi.org/10.1109/ijcnn.2004.1381065","mag":"2167656351"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2004.1381065","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1381065","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","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/A5027456427","display_name":"Steffen Hohmann","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128947","display_name":"Kirchhoff (Germany)","ror":"https://ror.org/031fvch84","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210128947"]},{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"S.G. Hohmann","raw_affiliation_strings":["Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany"],"affiliations":[{"raw_affiliation_string":"Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909","https://openalex.org/I4210128947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000052788","display_name":"Johannes Fieres","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128947","display_name":"Kirchhoff (Germany)","ror":"https://ror.org/031fvch84","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210128947"]},{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"J. Fieres","raw_affiliation_strings":["Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany"],"affiliations":[{"raw_affiliation_string":"Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909","https://openalex.org/I4210128947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050974988","display_name":"Karlheinz Meier","orcid":"https://orcid.org/0000-0001-7587-3808"},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]},{"id":"https://openalex.org/I4210128947","display_name":"Kirchhoff (Germany)","ror":"https://ror.org/031fvch84","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210128947"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"K. Meier","raw_affiliation_strings":["Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany"],"affiliations":[{"raw_affiliation_string":"Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909","https://openalex.org/I4210128947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022054975","display_name":"Johannes Schemmel","orcid":"https://orcid.org/0000-0003-1440-4375"},"institutions":[{"id":"https://openalex.org/I4210128947","display_name":"Kirchhoff (Germany)","ror":"https://ror.org/031fvch84","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210128947"]},{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"J. Schemmel","raw_affiliation_strings":["Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany"],"affiliations":[{"raw_affiliation_string":"Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909","https://openalex.org/I4210128947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039703417","display_name":"Tillmann Schmitz","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128947","display_name":"Kirchhoff (Germany)","ror":"https://ror.org/031fvch84","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210128947"]},{"id":"https://openalex.org/I85384741","display_name":"Heidelberg University","ror":"https://ror.org/04rcqnp59","country_code":"US","type":"education","lineage":["https://openalex.org/I85384741"]},{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"T. Schmitz","raw_affiliation_strings":["Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany","Ruprecht Karls Universitat Heidelberg, Heidelberg, Baden-W\u00c3\u00bcrttemberg, DE","Ruprecht Karls Universitat Heidelberg, Heidelberg, Baden-W\u00fcrttemberg, DE"],"affiliations":[{"raw_affiliation_string":"Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909","https://openalex.org/I4210128947"]},{"raw_affiliation_string":"Ruprecht Karls Universitat Heidelberg, Heidelberg, Baden-W\u00c3\u00bcrttemberg, DE","institution_ids":["https://openalex.org/I85384741"]},{"raw_affiliation_string":"Ruprecht Karls Universitat Heidelberg, Heidelberg, Baden-W\u00fcrttemberg, DE","institution_ids":["https://openalex.org/I85384741"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055974766","display_name":"F. Schumann","orcid":null},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]},{"id":"https://openalex.org/I4210128947","display_name":"Kirchhoff (Germany)","ror":"https://ror.org/031fvch84","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210128947"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"F. Schumann","raw_affiliation_strings":["Kirchhoff Inst. for Phys., Heidelberg Univ., Germany"],"affiliations":[{"raw_affiliation_string":"Kirchhoff Inst. for Phys., Heidelberg Univ., Germany","institution_ids":["https://openalex.org/I4210128947","https://openalex.org/I223822909"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5027456427"],"corresponding_institution_ids":["https://openalex.org/I223822909","https://openalex.org/I4210128947"],"apc_list":null,"apc_paid":null,"fwci":0.9134,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.82504185,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"4","issue":null,"first_page":"2647","last_page":"2652"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9994000196456909,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9994000196456909,"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":0.9987000226974487,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9939000010490417,"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":0.8280589580535889},{"id":"https://openalex.org/keywords/coprocessor","display_name":"Coprocessor","score":0.802667498588562},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6911196112632751},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6172041893005371},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.547539234161377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.540895938873291},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49766805768013},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.4508202373981476},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44891366362571716},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.44479554891586304},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.43960756063461304},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.41865095496177673},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.19665062427520752}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8280589580535889},{"id":"https://openalex.org/C86111242","wikidata":"https://www.wikidata.org/wiki/Q859595","display_name":"Coprocessor","level":2,"score":0.802667498588562},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6911196112632751},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6172041893005371},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.547539234161377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.540895938873291},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49766805768013},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.4508202373981476},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44891366362571716},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.44479554891586304},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.43960756063461304},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.41865095496177673},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.19665062427520752},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2004.1381065","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1381065","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W88442108","https://openalex.org/W133648044","https://openalex.org/W1581406946","https://openalex.org/W1820256006","https://openalex.org/W1856242899","https://openalex.org/W2066922849","https://openalex.org/W2124290836","https://openalex.org/W2125523964","https://openalex.org/W2130257290","https://openalex.org/W2134514463","https://openalex.org/W2143802925","https://openalex.org/W2158120166","https://openalex.org/W6603530089","https://openalex.org/W6634563840","https://openalex.org/W6638563403","https://openalex.org/W6678489563","https://openalex.org/W6683473195"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"This":[0],"work":[1],"presents":[2],"an":[3,116],"incremental":[4],"training":[5,28,79,114],"approach":[6],"that":[7,57,76,91],"allows":[8],"for":[9,83],"the":[10,19,46,58,77,98,106,110,113,123,126],"use":[11,84],"of":[12,21,35,52,125],"simple":[13],"evolutionary":[14,94],"algorithms":[15,95],"to":[16,50,68,108,121],"efficiently":[17],"train":[18],"weights":[20],"fast":[22],"mixed-signal":[23],"hardware":[24,60,128],"neural":[25,61,127],"networks.":[26],"The":[27],"strategy":[29,80],"is":[30,73,81,119],"tested":[31],"on":[32],"a":[33,88,102],"set":[34],"common":[36],"classification":[37],"benchmark":[38],"problems":[39],"(E.coli,":[40],"yeast,":[41],"thyroid":[42],"and":[43,45],"wine)":[44],"results":[47],"are":[48],"comparable":[49],"those":[51],"other":[53],"investigations.":[54],"They":[55],"demonstrate":[56],"used":[59],"network":[62],"architecture":[63],"can":[64],"successfully":[65],"be":[66],"trained":[67],"solve":[69],"real-world":[70],"problems.":[71],"It":[72],"also":[74],"shown":[75],"presented":[78],"suited":[82],"in":[85],"conjunction":[86],"with":[87],"specialized":[89],"coprocessor":[90,111],"speeds":[92],"up":[93],"by":[96],"performing":[97],"genetic":[99],"operations":[100],"within":[101],"configurable":[103],"logic.":[104],"With":[105],"ability":[107],"integrate":[109],"into":[112],"strategy,":[115],"important":[117],"prerequisite":[118],"fulfilled":[120],"exploit":[122],"speed":[124],"during":[129],"training.":[130]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}