{"id":"https://openalex.org/W4283076403","doi":"https://doi.org/10.1016/j.neucom.2022.06.035","title":"Variants of recurrent learning vector quantization","display_name":"Variants of recurrent learning vector quantization","publication_year":2022,"publication_date":"2022-06-18","ids":{"openalex":"https://openalex.org/W4283076403","doi":"https://doi.org/10.1016/j.neucom.2022.06.035"},"language":"en","primary_location":{"id":"doi:10.1016/j.neucom.2022.06.035","doi":"https://doi.org/10.1016/j.neucom.2022.06.035","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.neucom.2022.06.035","pdf_url":null,"source":{"id":"https://openalex.org/S45693802","display_name":"Neurocomputing","issn_l":"0925-2312","issn":["0925-2312","1872-8286"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","ccf-c","cwts-core","dongbi-b","doyens","jufo-2","ki-jl-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neurocomputing","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5041833018","display_name":"Jensun Ravichandran","orcid":"https://orcid.org/0000-0002-9137-1418","observed_orcids":["https://orcid.org/0000-0002-9137-1418"]},"institutions":[{"id":"https://openalex.org/I116397343","display_name":"Hochschule Mittweida","ror":"https://ror.org/024ga3r86","country_code":"DE","type":"education","lineage":["https://openalex.org/I116397343"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Jensun Ravichandran","raw_affiliation_strings":["University of Applied Sciences Mittweida, Saxony, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences Mittweida, Saxony, Germany","institution_ids":["https://openalex.org/I116397343"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084823973","display_name":"Marika Kaden","orcid":"https://orcid.org/0000-0002-2849-3463","observed_orcids":["https://orcid.org/0000-0002-2849-3463"]},"institutions":[{"id":"https://openalex.org/I116397343","display_name":"Hochschule Mittweida","ror":"https://ror.org/024ga3r86","country_code":"DE","type":"education","lineage":["https://openalex.org/I116397343"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marika Kaden","raw_affiliation_strings":["University of Applied Sciences Mittweida, Saxony, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences Mittweida, Saxony, Germany","institution_ids":["https://openalex.org/I116397343"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027248793","display_name":"Thomas Villmann","orcid":"https://orcid.org/0000-0001-6725-0141","observed_orcids":["https://orcid.org/0000-0001-6725-0141"]},"institutions":[{"id":"https://openalex.org/I116397343","display_name":"Hochschule Mittweida","ror":"https://ror.org/024ga3r86","country_code":"DE","type":"education","lineage":["https://openalex.org/I116397343"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Villmann","raw_affiliation_strings":["University of Applied Sciences Mittweida, Saxony, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences Mittweida, Saxony, Germany","institution_ids":["https://openalex.org/I116397343"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5041833018"],"corresponding_institution_ids":["https://openalex.org/I116397343"],"apc_list":{"value":2470,"currency":"USD","value_usd":2470},"apc_paid":null,"fwci":0.6022,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.65018848,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"502","issue":null,"first_page":"27","last_page":"36"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9976000189781189,"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":0.9976000189781189,"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":0.0010999999940395355,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/learning-vector-quantization","display_name":"learning vector quantization","score":0.8450000286102295},{"id":"https://openalex.org/keywords/generalized-learning-vector-quantization","display_name":"generalized learning vector quantization","score":0.953000009059906},{"id":"https://openalex.org/keywords/recurrent-neural-networks","display_name":"recurrent neural networks","score":0.8489999771118164},{"id":"https://openalex.org/keywords/sequence-classification","display_name":"sequence classification","score":0.6869999766349792},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"multi-class classification","score":0.7739999890327454},{"id":"https://openalex.org/keywords/raw-sequence-data","display_name":"raw sequence data","score":0.6729999780654907}],"concepts":[{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.9738628268241882},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.695004403591156},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6908501982688904},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6412596106529236},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5668541789054871},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5621992945671082},{"id":"https://openalex.org/C93372532","wikidata":"https://www.wikidata.org/wiki/Q6552455","display_name":"Linde\u2013Buzo\u2013Gray algorithm","level":3,"score":0.5322888493537903},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5117725729942322},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4000169336795807},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2747044563293457},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.neucom.2022.06.035","doi":"https://doi.org/10.1016/j.neucom.2022.06.035","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.neucom.2022.06.035","pdf_url":null,"source":{"id":"https://openalex.org/S45693802","display_name":"Neurocomputing","issn_l":"0925-2312","issn":["0925-2312","1872-8286"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","ccf-c","cwts-core","dongbi-b","doyens","jufo-2","ki-jl-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neurocomputing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320338080","display_name":"European Social Fund","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W108448858","https://openalex.org/W950853366","https://openalex.org/W1496343492","https://openalex.org/W1533861849","https://openalex.org/W1712368225","https://openalex.org/W2006493416","https://openalex.org/W2039434802","https://openalex.org/W2064675550","https://openalex.org/W2079587596","https://openalex.org/W2094150678","https://openalex.org/W2095705004","https://openalex.org/W2109993655","https://openalex.org/W2123749980","https://openalex.org/W2127589108","https://openalex.org/W2149608381","https://openalex.org/W2171590421","https://openalex.org/W2557283755","https://openalex.org/W2765813195","https://openalex.org/W2902596607","https://openalex.org/W2914512494","https://openalex.org/W2945976633","https://openalex.org/W2964121744","https://openalex.org/W2964256412","https://openalex.org/W2970917186","https://openalex.org/W2970971581","https://openalex.org/W3022838614","https://openalex.org/W3101316986","https://openalex.org/W3205134435","https://openalex.org/W3205709663","https://openalex.org/W6600755281","https://openalex.org/W6679338098"],"related_works":["https://openalex.org/W3205134435","https://openalex.org/W6929036449","https://openalex.org/W3006084694","https://openalex.org/W2561360825","https://openalex.org/W2151941540","https://openalex.org/W1444353813","https://openalex.org/W2116201135","https://openalex.org/W4240888499","https://openalex.org/W1569335651","https://openalex.org/W108285666"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2022-06-19T00:00:00"}
