{"id":"https://openalex.org/W2097238256","doi":"https://doi.org/10.1109/ijcnn.2009.5178913","title":"Feed-forward network training using optimal input gains","display_name":"Feed-forward network training using optimal input gains","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2097238256","doi":"https://doi.org/10.1109/ijcnn.2009.5178913","mag":"2097238256"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2009.5178913","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178913","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","raw_type":"proceedings-article"},"type":"conference-paper","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/A5036559796","display_name":"Sanjeev S. Malalur","orcid":null},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanjeev S. Malalur","raw_affiliation_strings":["Electrical Engineering Department, University of Technology, Arlington, TX, USA","Electrical Engineering Department, University of Texas at Arlington, 76010, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, University of Technology, Arlington, TX, USA","institution_ids":["https://openalex.org/I189196454"]},{"raw_affiliation_string":"Electrical Engineering Department, University of Texas at Arlington, 76010, USA","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114046112","display_name":"M.T. Manry","orcid":null},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Manry","raw_affiliation_strings":["Electrical Engineering Department, University of Technology, Arlington, TX, USA","Electrical Engineering Department, University of Texas at Arlington, 76010, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, University of Technology, Arlington, TX, USA","institution_ids":["https://openalex.org/I189196454"]},{"raw_affiliation_string":"Electrical Engineering Department, University of Texas at Arlington, 76010, USA","institution_ids":["https://openalex.org/I189196454"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I189196454"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":null,"first_page":"1953","last_page":"1960"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","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/T11447","display_name":"Blind Source Separation Techniques","score":0.9595000147819519,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9312000274658203,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/diagonal","display_name":"Diagonal","score":0.6998164653778076},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6522063612937927},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5455583333969116},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5326699018478394},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48584386706352234},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4783579707145691},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4594403803348541},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.4587476849555969},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.44179460406303406},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.41133809089660645},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3624357581138611},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3406651020050049},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2669593095779419},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.07393735647201538}],"concepts":[{"id":"https://openalex.org/C130367717","wikidata":"https://www.wikidata.org/wiki/Q189791","display_name":"Diagonal","level":2,"score":0.6998164653778076},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6522063612937927},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5455583333969116},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5326699018478394},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48584386706352234},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4783579707145691},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4594403803348541},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.4587476849555969},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.44179460406303406},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.41133809089660645},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3624357581138611},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3406651020050049},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2669593095779419},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.07393735647201538},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2009.5178913","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178913","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","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":21,"referenced_works":["https://openalex.org/W1500731913","https://openalex.org/W1777388371","https://openalex.org/W1985030154","https://openalex.org/W2020416411","https://openalex.org/W2045675031","https://openalex.org/W2046767802","https://openalex.org/W2092055157","https://openalex.org/W2100816322","https://openalex.org/W2100921332","https://openalex.org/W2103496339","https://openalex.org/W2113287505","https://openalex.org/W2141278204","https://openalex.org/W2146440428","https://openalex.org/W2154642048","https://openalex.org/W2155482699","https://openalex.org/W2347163592","https://openalex.org/W2766736793","https://openalex.org/W4206366638","https://openalex.org/W6673832546","https://openalex.org/W6675313117","https://openalex.org/W6682610290"],"related_works":["https://openalex.org/W2555356437","https://openalex.org/W2417891382","https://openalex.org/W2076543106","https://openalex.org/W4401177694","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2083196709","https://openalex.org/W2600618515","https://openalex.org/W4285523177"],"abstract_inverted_index":{"In":[0,74],"this":[1,47],"paper,":[2],"an":[3,70],"effective":[4],"batch":[5],"training":[6,91],"algorithm":[7,83],"is":[8,43,49,61,78,84],"developed":[9],"for":[10,40,65],"feed-forward":[11],"networks":[12],"such":[13],"as":[14],"the":[15,19,29,41,53,57,66,81],"multilayer":[16],"perceptron.":[17],"First,":[18],"effects":[20],"of":[21,31,46],"input":[22,54,67],"transforms":[23],"are":[24],"reviewed":[25],"and":[26,69,93],"explained,":[27],"using":[28],"concept":[30],"equivalent":[32,50],"networks.":[33],"Next,":[34],"a":[35,85],"non-singular":[36],"diagonal":[37],"transform":[38,48],"matrix":[39],"inputs":[42],"proposed.":[44],"Use":[45],"to":[51,63],"altering":[52],"gains":[55,68],"in":[56],"network.":[58],"Newton's":[59],"method":[60],"used":[62],"solve":[64],"optimal":[71],"learning":[72],"factor.":[73],"several":[75],"examples,":[76],"it":[77],"shown":[79],"that":[80],"final":[82],"reasonable":[86],"compromise":[87],"between":[88],"first":[89],"order":[90],"methods":[92],"Levenburg-Marquardt.":[94]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}