{"id":"https://openalex.org/W3106932805","doi":"https://doi.org/10.1109/icce-taiwan49838.2020.9258202","title":"Influence of Recognition Performance on Recurrent Neural Network Using Phase-Change Memory as Synapses","display_name":"Influence of Recognition Performance on Recurrent Neural Network Using Phase-Change Memory as Synapses","publication_year":2020,"publication_date":"2020-09-28","ids":{"openalex":"https://openalex.org/W3106932805","doi":"https://doi.org/10.1109/icce-taiwan49838.2020.9258202","mag":"3106932805"},"language":"en","primary_location":{"id":"doi:10.1109/icce-taiwan49838.2020.9258202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan49838.2020.9258202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","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/A5026581043","display_name":"Tomohiro Takahashi","orcid":"https://orcid.org/0000-0003-1325-0693"},"institutions":[{"id":"https://openalex.org/I159385669","display_name":"Chiba University","ror":"https://ror.org/01hjzeq58","country_code":"JP","type":"education","lineage":["https://openalex.org/I159385669"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Tomohiro Takahashi","raw_affiliation_strings":["Graduate School of Science and Engineering, Chiba University, Chiba-shi, Chiba, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering, Chiba University, Chiba-shi, Chiba, Japan","institution_ids":["https://openalex.org/I159385669"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009094960","display_name":"Kazuteru Namba","orcid":"https://orcid.org/0000-0002-8316-7281"},"institutions":[{"id":"https://openalex.org/I159385669","display_name":"Chiba University","ror":"https://ror.org/01hjzeq58","country_code":"JP","type":"education","lineage":["https://openalex.org/I159385669"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuteru Namba","raw_affiliation_strings":["Graduate School of Engineering, Chiba University, Chiba-shi, Chiba, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Chiba University, Chiba-shi, Chiba, Japan","institution_ids":["https://openalex.org/I159385669"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026581043"],"corresponding_institution_ids":["https://openalex.org/I159385669"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.11636182,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9997000098228455,"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":0.9997000098228455,"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/T10320","display_name":"Neural Networks and Applications","score":0.998199999332428,"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/T12676","display_name":"Machine Learning and ELM","score":0.9970999956130981,"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":0.7594120502471924},{"id":"https://openalex.org/keywords/phase-change-memory","display_name":"Phase-change memory","score":0.6937850713729858},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6705370545387268},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.6496040225028992},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6310107111930847},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4513234496116638},{"id":"https://openalex.org/keywords/error-detection-and-correction","display_name":"Error detection and correction","score":0.4184276759624481},{"id":"https://openalex.org/keywords/weight-change","display_name":"Weight change","score":0.4141031503677368},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3472177982330322},{"id":"https://openalex.org/keywords/phase-change","display_name":"Phase change","score":0.31914645433425903},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.17461782693862915},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07908821105957031}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7594120502471924},{"id":"https://openalex.org/C64142963","wikidata":"https://www.wikidata.org/wiki/Q1153902","display_name":"Phase-change memory","level":3,"score":0.6937850713729858},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6705370545387268},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.6496040225028992},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6310107111930847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4513234496116638},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.4184276759624481},{"id":"https://openalex.org/C3017894415","wikidata":"https://www.wikidata.org/wiki/Q7979883","display_name":"Weight change","level":4,"score":0.4141031503677368},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3472177982330322},{"id":"https://openalex.org/C133256868","wikidata":"https://www.wikidata.org/wiki/Q7180940","display_name":"Phase change","level":2,"score":0.31914645433425903},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.17461782693862915},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07908821105957031},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C511355011","wikidata":"https://www.wikidata.org/wiki/Q12174","display_name":"Obesity","level":2,"score":0.0},{"id":"https://openalex.org/C61696701","wikidata":"https://www.wikidata.org/wiki/Q770766","display_name":"Engineering physics","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C544821477","wikidata":"https://www.wikidata.org/wiki/Q718113","display_name":"Weight loss","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce-taiwan49838.2020.9258202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan49838.2020.9258202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W2905229633","https://openalex.org/W2963566954"],"related_works":["https://openalex.org/W2104335563","https://openalex.org/W2791399427","https://openalex.org/W2317775939","https://openalex.org/W2746127745","https://openalex.org/W2956935485","https://openalex.org/W2029580196","https://openalex.org/W2003932139","https://openalex.org/W2163661908","https://openalex.org/W3144682259","https://openalex.org/W3093908679"],"abstract_inverted_index":{"This":[0],"paper":[1],"simulates":[2],"the":[3,22,44,54,59,64,74,77],"influence":[4],"of":[5,8,16],"recognition":[6],"performance":[7],"using":[9],"a":[10,17,25],"virtual":[11],"phase-change":[12,41],"memory":[13],"as":[14],"weight":[15],"recurrent":[18],"neural":[19,26],"network.":[20],"In":[21,43],"first":[23],"experiment,":[24],"network":[27],"did":[28],"not":[29],"learn":[30],"well":[31],"due":[32],"to":[33],"NaN":[34],"error":[35,39,56,71],"caused":[36,73],"by":[37],"write":[38,55,70],"in":[40],"memory.":[42],"second":[45],"and":[46,58],"later":[47],"experiments,":[48],"there":[49],"was":[50],"no":[51],"correlation":[52],"between":[53],"rate":[57,72],"validation":[60],"loss.":[61],"However,":[62],"when":[63],"learning":[65],"results":[66],"were":[67],"output,":[68],"higher":[69],"less":[75],"successful":[76],"learning.":[78]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}