{"id":"https://openalex.org/W2095271550","doi":"https://doi.org/10.1002/scj.4690210908","title":"A method for designing neural networks using nonlinear multivariate analysis\u2014application to speaker\u2010independent vowel recognition","display_name":"A method for designing neural networks using nonlinear multivariate analysis\u2014application to speaker\u2010independent vowel recognition","publication_year":1990,"publication_date":"1990-01-01","ids":{"openalex":"https://openalex.org/W2095271550","doi":"https://doi.org/10.1002/scj.4690210908","mag":"2095271550"},"language":"en","primary_location":{"id":"doi:10.1002/scj.4690210908","is_oa":false,"landing_page_url":"https://doi.org/10.1002/scj.4690210908","pdf_url":null,"source":{"id":"https://openalex.org/S58208175","display_name":"Systems and Computers in Japan","issn_l":"0882-1666","issn":["0882-1666","1520-684X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems and Computers in Japan","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/A5078342732","display_name":"Toshio Irino","orcid":"https://orcid.org/0000-0002-7691-4189"},"institutions":[{"id":"https://openalex.org/I4210105847","display_name":"NTT Basic Research Laboratories","ror":"https://ror.org/01m2pas06","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210105847"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toshio Irino","raw_affiliation_strings":["NTT Basic Research Laboratories, Musashino, Japan 180"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Basic Research Laboratories, Musashino, Japan 180","institution_ids":["https://openalex.org/I4210105847"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072749858","display_name":"Hideki Kawahara","orcid":"https://orcid.org/0000-0001-9360-5700"},"institutions":[{"id":"https://openalex.org/I4210105847","display_name":"NTT Basic Research Laboratories","ror":"https://ror.org/01m2pas06","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210105847"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hideki Kawahara","raw_affiliation_strings":["NTT Basic Research Laboratories, Musashino, Japan 180"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Basic Research Laboratories, Musashino, Japan 180","institution_ids":["https://openalex.org/I4210105847"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210105847"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.18909073,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":"9","first_page":"80","last_page":"88"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9984999895095825,"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":0.9984999895095825,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.972599983215332,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9660999774932861,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/artificial-neural-network","display_name":"Artificial neural network","score":0.7088437676429749},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6401880383491516},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5603849291801453},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5462980270385742},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5394651889801025},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4943983554840088},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48904451727867126},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.48719900846481323},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4560728669166565},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.4445480704307556},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.4286747872829437},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30375057458877563},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2418772578239441},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24115276336669922},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20159485936164856}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7088437676429749},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6401880383491516},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5603849291801453},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5462980270385742},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5394651889801025},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4943983554840088},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48904451727867126},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.48719900846481323},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4560728669166565},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.4445480704307556},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.4286747872829437},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30375057458877563},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2418772578239441},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24115276336669922},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20159485936164856},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/scj.4690210908","is_oa":false,"landing_page_url":"https://doi.org/10.1002/scj.4690210908","pdf_url":null,"source":{"id":"https://openalex.org/S58208175","display_name":"Systems and Computers in Japan","issn_l":"0882-1666","issn":["0882-1666","1520-684X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems and Computers in Japan","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W94523489","https://openalex.org/W1571573569","https://openalex.org/W2058261204","https://openalex.org/W3207342693","https://openalex.org/W4300402905"],"related_works":["https://openalex.org/W4239286941","https://openalex.org/W2088845016","https://openalex.org/W589102260","https://openalex.org/W1966421350","https://openalex.org/W1868434454","https://openalex.org/W4366985237","https://openalex.org/W4367365565","https://openalex.org/W2128396103","https://openalex.org/W4367299891","https://openalex.org/W2810569973"],"abstract_inverted_index":{"Abstract":[0],"This":[1],"paper":[2,87],"proposes":[3],"a":[4,8,21,63,138],"method":[5,39,65,94],"of":[6,30,50],"constructing":[7],"multilayered":[9,52],"neural":[10,53,75],"network,":[11],"using":[12],"the":[13,26,37,48,51,74,79,84,89,92,96,99,105,110,117,121,126,141,145,153,158,166,173,176],"multiple":[14,101],"logistic":[15,28],"model":[16,19,57],"(MLM).":[17],"The":[18,41,56],"is":[20,34,135,144,149,162,169],"nonlinear":[22],"multivariate":[23],"analysis":[24,103],"considering":[25],"output":[27],"function":[29],"each":[31],"unit,":[32],"which":[33],"used":[35],"in":[36],"back\u2010propagation":[38],"(BP).":[40],"idea":[42],"can":[43,58],"be":[44,60],"applied":[45,150],"directly":[46],"to":[47,66],"determination":[49],"network":[54,76],"structure.":[55,77],"also":[59,164],"utilized":[61],"as":[62,70,83,116,137],"systematic":[64],"introduce":[67],"such":[68],"information":[69,156],"pattern":[71],"distribution":[72,155],"into":[73],"Considering":[78],"speaker\u2010independent":[80],"vowel":[81],"recognition":[82,142],"problem,":[85],"this":[86],"compares":[88],"results":[90],"by":[91,98,107,123,130,157],"proposed":[93,159],"(MLM),":[95],"construction":[97],"linear":[100],"regression":[102],"(MRA),":[104],"learning":[106,122],"BP":[108,124,148],"with":[109,125,172,175],"weight":[111,128,178],"being":[112,179],"defined":[113,180],"at":[114,181],"random":[115],"initial":[118,127,177],"value,":[119],"and":[120],"determined":[129],"MLM":[131],"or":[132],"MRA.":[133],"It":[134,161],"seen":[136,163],"result":[139],"that":[140,165],"rate":[143],"best":[146],"when":[147],"after":[151],"introducing":[152],"speaker":[154],"method.":[160],"computation":[167],"time":[168],"reduced":[170],"compared":[171],"BP,":[174],"random.":[182]},"counts_by_year":[],"updated_date":"2026-06-23T06:36:01.041984","created_date":"2025-10-10T00:00:00"}
