{"id":"https://openalex.org/W2342814244","doi":"https://doi.org/10.1109/tnnls.2015.2513365","title":"QRNN: $q$ -Generalized Random Neural Network","display_name":"QRNN: $q$ -Generalized Random Neural Network","publication_year":2016,"publication_date":"2016-01-15","ids":{"openalex":"https://openalex.org/W2342814244","doi":"https://doi.org/10.1109/tnnls.2015.2513365","mag":"2342814244","pmid":"https://pubmed.ncbi.nlm.nih.gov/26780820"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2015.2513365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2015.2513365","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5102721508","display_name":"Du\u0161an Sto\u0161i\u0107","orcid":"https://orcid.org/0000-0003-0337-8511"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Dusan Stosic","raw_affiliation_strings":["Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife PE, Brazil"],"affiliations":[{"raw_affiliation_string":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife PE, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026607041","display_name":"Darko Sto\u0161i\u0107","orcid":null},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Darko Stosic","raw_affiliation_strings":["Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife PE, Brazil"],"affiliations":[{"raw_affiliation_string":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife PE, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086345001","display_name":"Cleber Zanchettin","orcid":"https://orcid.org/0000-0001-6421-9747"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Cleber Zanchettin","raw_affiliation_strings":["Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife PE, Brazil"],"affiliations":[{"raw_affiliation_string":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife PE, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025550530","display_name":"Teresa B. Ludermir","orcid":"https://orcid.org/0000-0002-8980-6742"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Teresa Ludermir","raw_affiliation_strings":["Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife PE, Brazil"],"affiliations":[{"raw_affiliation_string":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife PE, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042925476","display_name":"Borko Sto\u0161i\u0107","orcid":"https://orcid.org/0000-0001-5031-6968"},"institutions":[{"id":"https://openalex.org/I62921916","display_name":"Universidade Federal Rural de Pernambuco","ror":"https://ror.org/02ksmb993","country_code":"BR","type":"education","lineage":["https://openalex.org/I62921916"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Borko Stosic","raw_affiliation_strings":["Departamento de Estat\u00edstica e Inform\u00e1tica, Universidade Federal Rural de Pernambuco, Recife PE, Brazil"],"affiliations":[{"raw_affiliation_string":"Departamento de Estat\u00edstica e Inform\u00e1tica, Universidade Federal Rural de Pernambuco, Recife PE, Brazil","institution_ids":["https://openalex.org/I62921916"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102721508"],"corresponding_institution_ids":["https://openalex.org/I25112270"],"apc_list":null,"apc_paid":null,"fwci":4.2848,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.94748573,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"28","issue":"2","first_page":"383","last_page":"390"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9993000030517578,"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/T10057","display_name":"Face and Expression Recognition","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.6163638830184937},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40794065594673157},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3902597725391388},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.37480902671813965},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24458813667297363},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.22117391228675842}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6163638830184937},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40794065594673157},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3902597725391388},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.37480902671813965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24458813667297363},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.22117391228675842}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2015.2513365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2015.2513365","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:26780820","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26780820","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G7876160122","display_name":null,"funder_award_id":"302526/2011-0","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W94523489","https://openalex.org/W101663867","https://openalex.org/W107370486","https://openalex.org/W150571132","https://openalex.org/W1480102187","https://openalex.org/W1554663460","https://openalex.org/W1731748326","https://openalex.org/W1974887910","https://openalex.org/W1983874169","https://openalex.org/W1988115241","https://openalex.org/W1992224053","https://openalex.org/W1996640396","https://openalex.org/W2016944307","https://openalex.org/W2025357764","https://openalex.org/W2069735905","https://openalex.org/W2106525823","https://openalex.org/W2111072639","https://openalex.org/W2113442785","https://openalex.org/W2114354594","https://openalex.org/W2137939562","https://openalex.org/W2138383519","https://openalex.org/W2153232138","https://openalex.org/W2153635508","https://openalex.org/W2155910151","https://openalex.org/W2998768810","https://openalex.org/W4252684946","https://openalex.org/W4388297464","https://openalex.org/W6604365512","https://openalex.org/W6637611448"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W1979597421","https://openalex.org/W2007980826","https://openalex.org/W2061531152","https://openalex.org/W3002753104","https://openalex.org/W2077600819","https://openalex.org/W2142036596","https://openalex.org/W2072657027"],"abstract_inverted_index":{"Artificial":[0],"neural":[1,55],"networks":[2],"(ANNs)":[3],"are":[4,131],"widely":[5],"used":[6,132],"in":[7,22,171,180],"applications":[8],"with":[9,58,119,147,164],"complex":[10,97],"decision":[11,98],"boundaries.":[12],"A":[13],"large":[14],"number":[15],"of":[16,29,88,100,116,159,167,182],"activation":[17,61,149],"functions":[18,62],"have":[19],"been":[20,44],"proposed":[21,73],"the":[23,30,81,86,93,105,114,140,160,165],"literature":[24],"to":[25,46,95,112,133],"achieve":[26],"better":[27,144],"representations":[28],"observed":[31],"data.":[32],"However,":[33],"only":[34],"a":[35,53,177],"few":[36],"works":[37],"employ":[38],"Tsallis":[39,70],"statistics,":[40],"which":[41,84,172],"has":[42,92],"successfully":[43],"applied":[45],"various":[47],"other":[48,123],"fields.":[49],"This":[50,90],"paper":[51],"presents":[52],"random":[54],"network":[56],"(RNN)":[57],"q":[59,64,79],"-Gaussian":[60],"[":[63],"-generalized":[65],"RNN":[66],"(QRNN)]":[67],"based":[68],"on":[69],"statistics.":[71],"The":[72],"method":[74],"employs":[75],"an":[76],"additional":[77],"parameter":[78],"(called":[80],"entropic":[82,106],"index)":[83],"reflects":[85],"degree":[87],"nonextensivity.":[89],"approach":[91],"flexibility":[94],"model":[96],"boundaries":[99],"different":[101,148],"shapes":[102],"by":[103],"varying":[104],"index.":[107],"We":[108],"conduct":[109],"numerical":[110],"experiments":[111],"analyze":[113],"efficiency":[115],"QRNN":[117,141,156],"compared":[118,161],"RNNs":[120,146],"and":[121,129,137,185],"several":[122],"classical":[124,162],"methods.":[125],"Statistical":[126],"tests":[127],"(Wilcoxon":[128],"Friedman)":[130],"validate":[134],"our":[135],"results":[136],"show":[138],"that":[139,155],"performs":[142],"significantly":[143],"than":[145],"functions.":[150],"In":[151],"addition,":[152],"we":[153],"find":[154],"outperforms":[157],"many":[158],"methods,":[163],"exception":[166],"support":[168],"vector":[169],"machines,":[170],"case":[173],"it":[174],"still":[175],"exhibits":[176],"substantial":[178],"advantage":[179],"terms":[181],"implementation":[183],"simplicity":[184],"speed.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
