{"id":"https://openalex.org/W2555012488","doi":"https://doi.org/10.1109/ijcnn.2016.7727737","title":"GPU simulator of multilayer neural network based on multi-valued neurons","display_name":"GPU simulator of multilayer neural network based on multi-valued neurons","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2555012488","doi":"https://doi.org/10.1109/ijcnn.2016.7727737","mag":"2555012488"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727737","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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/A5089090103","display_name":"Christian Hacker","orcid":"https://orcid.org/0000-0003-4920-9289"},"institutions":[{"id":"https://openalex.org/I51380931","display_name":"Texas A&M University \u2013 Texarkana","ror":"https://ror.org/01x3z9745","country_code":"US","type":"education","lineage":["https://openalex.org/I51380931"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christian Hacker","raw_affiliation_strings":["Texas A&M University-Texarkana, Texarkana, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas A&M University-Texarkana, Texarkana, TX, USA","institution_ids":["https://openalex.org/I51380931"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052101553","display_name":"Igor Aizenberg","orcid":"https://orcid.org/0000-0002-5994-6568"},"institutions":[{"id":"https://openalex.org/I55707380","display_name":"Manhattan University","ror":"https://ror.org/02xhnzg94","country_code":"US","type":"education","lineage":["https://openalex.org/I55707380"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Igor Aizenberg","raw_affiliation_strings":["Manhattan College, Riverdale, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Manhattan College, Riverdale, NY, USA","institution_ids":["https://openalex.org/I55707380"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103288609","display_name":"J. Gaines Wilson","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeff Wilson","raw_affiliation_strings":["Dallas, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dallas, TX, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7666,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.89718285,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"196","issue":null,"first_page":"4125","last_page":"4132"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9979000091552734,"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"}},{"id":"https://openalex.org/T11034","display_name":"Digital Filter Design and Implementation","score":0.9782999753952026,"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/bottleneck","display_name":"Bottleneck","score":0.8238470554351807},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.80808424949646},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6984001398086548},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5619175434112549},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5412478446960449},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.48751208186149597},{"id":"https://openalex.org/keywords/computer-architecture-simulator","display_name":"Computer architecture simulator","score":0.474751740694046},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.4293440878391266},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4195346236228943},{"id":"https://openalex.org/keywords/feedforward-neural-network","display_name":"Feedforward neural network","score":0.41405731439590454},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.2781260013580322},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.18640825152397156},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09291127324104309}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.8238470554351807},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.80808424949646},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6984001398086548},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5619175434112549},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5412478446960449},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.48751208186149597},{"id":"https://openalex.org/C201203610","wikidata":"https://www.wikidata.org/wiki/Q5157524","display_name":"Computer architecture simulator","level":2,"score":0.474751740694046},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4293440878391266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4195346236228943},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.41405731439590454},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2781260013580322},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.18640825152397156},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09291127324104309},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727737","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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":36,"referenced_works":["https://openalex.org/W118053813","https://openalex.org/W1585539754","https://openalex.org/W1594058661","https://openalex.org/W1978437915","https://openalex.org/W1984222112","https://openalex.org/W1985462363","https://openalex.org/W2019747896","https://openalex.org/W2021173614","https://openalex.org/W2037642501","https://openalex.org/W2047063224","https://openalex.org/W2047515252","https://openalex.org/W2048361500","https://openalex.org/W2050111479","https://openalex.org/W2056370875","https://openalex.org/W2058399474","https://openalex.org/W2081097129","https://openalex.org/W2089823888","https://openalex.org/W2105050785","https://openalex.org/W2109337973","https://openalex.org/W2125789994","https://openalex.org/W2134563598","https://openalex.org/W2135858797","https://openalex.org/W2136892987","https://openalex.org/W2146292423","https://openalex.org/W2156869838","https://openalex.org/W2161694749","https://openalex.org/W2168976537","https://openalex.org/W2178055113","https://openalex.org/W2183227662","https://openalex.org/W2268045897","https://openalex.org/W2476841360","https://openalex.org/W3120740533","https://openalex.org/W6676463140","https://openalex.org/W6686281057","https://openalex.org/W6693358704","https://openalex.org/W6788247690"],"related_works":["https://openalex.org/W1657880117","https://openalex.org/W2595172197","https://openalex.org/W2127970246","https://openalex.org/W2084856301","https://openalex.org/W1001352512","https://openalex.org/W4382618745","https://openalex.org/W973676589","https://openalex.org/W2377087609","https://openalex.org/W1812866462","https://openalex.org/W1953410804"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"consider":[4],"principles":[5,112],"of":[6,11,15,53,79,100,113,117],"design":[7],"and":[8,92,119],"basic":[9,111],"fundamentals":[10],"a":[12,26,31,36,43,47,70,77,169],"GPU":[13,115,142,170],"simulator":[14,116],"the":[16,51,114,132,134,137,156],"multilayer":[17],"neural":[18,38,54,73,85],"network":[19,39,135],"with":[20],"multi-valued":[21],"neurons":[22],"(MLMVN).":[23],"Slowing":[24],"down":[25],"learning":[27,33,91,158],"process":[28],"due":[29],"to":[30,65,83,149],"big":[32,37],"dataset":[34],"and/or":[35],"needed":[40],"for":[41,56,155],"solving":[42,57],"certain":[44],"problem":[45],"is":[46,63,69,129,140,145],"potential":[48],"bottleneck":[49],"preventing":[50],"use":[52],"networks":[55],"some":[58],"challenging":[59],"problems.":[60],"The":[61],"same":[62],"related":[64],"deep":[66],"learning.":[67],"MLMVN":[68,118,157],"feedforward":[71],"complex-valued":[72],"network,":[74],"which":[75,162],"has":[76],"number":[78],"advantages":[80,88],"when":[81],"compared":[82],"real-valued":[84],"networks.":[86],"These":[87],"include":[89],"derivative-free":[90],"significantly":[93],"better":[94],"generalization":[95],"capability.":[96],"To":[97],"extend":[98],"applicability":[99],"MLMVN,":[101],"its":[102,141],"GPU-based":[103],"software":[104],"implementation":[105],"shall":[106],"be":[107,153,165],"considered.":[108],"We":[109],"present":[110],"how":[120],"matrix":[121],"algebra":[122],"operations":[123],"are":[124,172],"specifically":[125],"employed":[126],"there.":[127],"It":[128,144],"shown":[130,146],"that":[131,147],"bigger":[133],"is,":[136],"more":[138],"beneficial":[139],"implementation.":[143],"up":[148],"32\u00d7":[150],"acceleration":[151],"can":[152],"achieved":[154],"process.":[159],"Some":[160],"applications,":[161],"could":[163],"not":[164],"even":[166],"considered":[167],"without":[168],"simulator,":[171],"also":[173],"presented.":[174]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
