{"id":"https://openalex.org/W2077493113","doi":"https://doi.org/10.1109/ijcnn.1990.137822","title":"MEKA-a fast, local algorithm for training feedforward neural networks","display_name":"MEKA-a fast, local algorithm for training feedforward neural networks","publication_year":1990,"publication_date":"1990-01-01","ids":{"openalex":"https://openalex.org/W2077493113","doi":"https://doi.org/10.1109/ijcnn.1990.137822","mag":"2077493113"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.1990.137822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.1990.137822","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"1990 IJCNN International Joint Conference on Neural Networks","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/A5055516208","display_name":"Sahil Shah","orcid":"https://orcid.org/0000-0001-5972-3199"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"S. Shah","raw_affiliation_strings":["Department of Electrical and Systems Engineering, University of Connecticut, Storrs, CT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Systems Engineering, University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082596053","display_name":"F. Palmieri","orcid":"https://orcid.org/0000-0003-3777-3501"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"F. Palmieri","raw_affiliation_strings":["Department of Electrical and Systems Engineering, University of Connecticut, Storrs, CT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Systems Engineering, University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5055516208"],"corresponding_institution_ids":["https://openalex.org/I140172145"],"apc_list":null,"apc_paid":null,"fwci":3.1131,"has_fulltext":false,"cited_by_count":64,"citation_normalized_percentile":{"value":0.92282405,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"41","last_page":"46 vol.3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.996399998664856,"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":0.995199978351593,"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/maxima-and-minima","display_name":"Maxima and minima","score":0.766730546951294},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7137019634246826},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.7010908722877502},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.682499349117279},{"id":"https://openalex.org/keywords/feedforward-neural-network","display_name":"Feedforward neural network","score":0.6720694303512573},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6614606976509094},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6590559482574463},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.613703727722168},{"id":"https://openalex.org/keywords/feed-forward","display_name":"Feed forward","score":0.582011342048645},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5380285382270813},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5145353674888611},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.46027207374572754},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3751961588859558},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1796661913394928},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1010168194770813}],"concepts":[{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.766730546951294},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7137019634246826},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.7010908722877502},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.682499349117279},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.6720694303512573},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6614606976509094},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6590559482574463},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.613703727722168},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.582011342048645},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5380285382270813},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5145353674888611},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.46027207374572754},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3751961588859558},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1796661913394928},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1010168194770813},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.1990.137822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.1990.137822","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"1990 IJCNN International Joint Conference on Neural Networks","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","score":0.7200000286102295,"display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W292716351","https://openalex.org/W1965324089","https://openalex.org/W1971129545","https://openalex.org/W2140207729","https://openalex.org/W2146528014","https://openalex.org/W2148845786","https://openalex.org/W2154642048","https://openalex.org/W2160699933","https://openalex.org/W2293807537","https://openalex.org/W3216584063"],"related_works":["https://openalex.org/W1535694475","https://openalex.org/W1965562977","https://openalex.org/W2135804779","https://openalex.org/W2093953062","https://openalex.org/W2115072676","https://openalex.org/W97768505","https://openalex.org/W2918103456","https://openalex.org/W2080531293","https://openalex.org/W4300200276","https://openalex.org/W1856772668"],"abstract_inverted_index":{"It":[0,34],"is":[1,14,35,58,87],"noted":[2],"that":[3],"the":[4,10,24,38,42,47,61,69,96,102,106,111],"training":[5],"of":[6,40,45,52,66,76,80,105,113],"feedforward":[7,32],"networks":[8],"using":[9],"conventional":[11],"backpropagation":[12],"algorithm":[13,28,57,73],"plagued":[15],"by":[16],"poor":[17],"convergence":[18,77],"and":[19,78],"misadjustment.":[20],"The":[21,56,64,89],"authors":[22],"introduce":[23],"multiple":[25],"extended":[26,71],"Kalman":[27,72],"(MEKA)":[29],"to":[30,95],"train":[31],"networks.":[33],"based":[36],"on":[37,83],"idea":[39],"partitioning":[41],"global":[43,70],"problem":[44],"finding":[46],"weights":[48],"into":[49,116],"a":[50,117],"set":[51],"manageable":[53],"nonlinear":[54,97],"subproblems.":[55],"local":[59,107,118],"at":[60],"neuron":[62],"level.":[63],"superiority":[65],"MEKA":[67],"over":[68],"in":[74],"terms":[75],"quality":[79],"solution":[81],"obtained":[82],"two":[84],"benchmark":[85],"problems":[86],"demonstrated.":[88],"superior":[90],"performance":[91,108],"can":[92],"be":[93],"attributed":[94],"localized":[98],"approach.":[99],"In":[100],"fact,":[101],"nonconvex":[103],"nature":[104],"surface":[109],"reduces":[110],"chances":[112],"getting":[114],"trapped":[115],"minima":[119]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}