{"id":"https://openalex.org/W2734797130","doi":"https://doi.org/10.1109/ijcnn.2017.7966170","title":"A quotient gradient method to train artificial neural networks","display_name":"A quotient gradient method to train artificial neural networks","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2734797130","doi":"https://doi.org/10.1109/ijcnn.2017.7966170","mag":"2734797130"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2017.7966170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966170","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5037189000","display_name":"Hamid Khodabandehlou","orcid":"https://orcid.org/0000-0001-7386-2785"},"institutions":[{"id":"https://openalex.org/I134113660","display_name":"University of Nevada, Reno","ror":"https://ror.org/01keh0577","country_code":"US","type":"education","lineage":["https://openalex.org/I134113660"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hamid Khodabandehlou","raw_affiliation_strings":["EBME Department, University of Nevada, Reno, Reno, Nevada"],"affiliations":[{"raw_affiliation_string":"EBME Department, University of Nevada, Reno, Reno, Nevada","institution_ids":["https://openalex.org/I134113660"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112230618","display_name":"Mohammad Sami Fadali","orcid":null},"institutions":[{"id":"https://openalex.org/I134113660","display_name":"University of Nevada, Reno","ror":"https://ror.org/01keh0577","country_code":"US","type":"education","lineage":["https://openalex.org/I134113660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammad Sami Fadali","raw_affiliation_strings":["EBME Department, University of Nevada, Reno, Reno, Nevada"],"affiliations":[{"raw_affiliation_string":"EBME Department, University of Nevada, Reno, Reno, Nevada","institution_ids":["https://openalex.org/I134113660"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5037189000"],"corresponding_institution_ids":["https://openalex.org/I134113660"],"apc_list":null,"apc_paid":null,"fwci":0.9751,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.8181482,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"1 39","issue":null,"first_page":"2576","last_page":"2581"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9987000226974487,"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":0.9987000226974487,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9807999730110168,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9455000162124634,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.8606210350990295},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7494181394577026},{"id":"https://openalex.org/keywords/quotient","display_name":"Quotient","score":0.7018168568611145},{"id":"https://openalex.org/keywords/gradient-method","display_name":"Gradient method","score":0.6235624551773071},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6098886132240295},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.5212850570678711},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.49548208713531494},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.46234479546546936},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4433954060077667},{"id":"https://openalex.org/keywords/feedforward-neural-network","display_name":"Feedforward neural network","score":0.4337748885154724},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3880046010017395},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3299596905708313},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22681525349617004}],"concepts":[{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.8606210350990295},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7494181394577026},{"id":"https://openalex.org/C199422724","wikidata":"https://www.wikidata.org/wiki/Q41118","display_name":"Quotient","level":2,"score":0.7018168568611145},{"id":"https://openalex.org/C115680565","wikidata":"https://www.wikidata.org/wiki/Q5977448","display_name":"Gradient method","level":2,"score":0.6235624551773071},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6098886132240295},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.5212850570678711},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.49548208713531494},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.46234479546546936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4433954060077667},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.4337748885154724},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3880046010017395},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3299596905708313},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22681525349617004},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2017.7966170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966170","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W40806228","https://openalex.org/W114517082","https://openalex.org/W140368079","https://openalex.org/W309725730","https://openalex.org/W1561520039","https://openalex.org/W1764573941","https://openalex.org/W1970271540","https://openalex.org/W2016879831","https://openalex.org/W2022740958","https://openalex.org/W2051812123","https://openalex.org/W2104934474","https://openalex.org/W2111639050","https://openalex.org/W2114112735","https://openalex.org/W2137983211","https://openalex.org/W2150354929","https://openalex.org/W2153795254","https://openalex.org/W2156151304","https://openalex.org/W2160208155","https://openalex.org/W2160570432","https://openalex.org/W2167002981","https://openalex.org/W2169762136","https://openalex.org/W2766736793","https://openalex.org/W4285719527","https://openalex.org/W6610992974","https://openalex.org/W6676981365","https://openalex.org/W6682610290","https://openalex.org/W6683561667"],"related_works":["https://openalex.org/W2115605526","https://openalex.org/W3093883775","https://openalex.org/W1539246760","https://openalex.org/W2786746258","https://openalex.org/W4225893763","https://openalex.org/W2788727425","https://openalex.org/W2405196115","https://openalex.org/W2104893957","https://openalex.org/W4402471162","https://openalex.org/W2971074373"],"abstract_inverted_index":{"In":[0],"this":[1],"study":[2],"we":[3],"introduce":[4],"a":[5,10,18,32],"new":[6],"approach":[7],"to":[8,77,81],"train":[9],"fully":[11],"recurrent":[12],"artificial":[13],"neural":[14],"network":[15,59],"by":[16],"solving":[17],"constraint":[19],"satisfaction":[20],"problem":[21,45],"using":[22],"the":[23,44,58,62],"quotient":[24,28,63],"gradient":[25,29,64],"method.":[26],"The":[27,72],"method":[30,65,73],"is":[31,74],"trajectory":[33],"based":[34,52],"methodology":[35],"for":[36],"global":[37,83],"optimization":[38,84],"that":[39,57],"does":[40],"not":[41],"suffer":[42],"from":[43],"of":[46],"local":[47],"minima":[48],"encountered":[49],"in":[50,79],"Newton":[51],"methods.":[53],"Simulation":[54],"results":[55],"show":[56],"trained":[60],"with":[61],"perform":[66],"better":[67],"than":[68],"traditional":[69],"error":[70],"backpropagation.":[71],"also":[75],"easier":[76],"implement":[78],"comparison":[80],"other":[82],"techniques":[85],"such":[86],"as":[87],"genetic":[88],"algorithms.":[89]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
