{"id":"https://openalex.org/W2113669863","doi":"https://doi.org/10.1109/nnsp.2002.1030033","title":"Modified Kalman filter based method for training state-recurrent multilayer perceptrons","display_name":"Modified Kalman filter based method for training state-recurrent multilayer perceptrons","publication_year":2003,"publication_date":"2003-06-25","ids":{"openalex":"https://openalex.org/W2113669863","doi":"https://doi.org/10.1109/nnsp.2002.1030033","mag":"2113669863"},"language":"en","primary_location":{"id":"doi:10.1109/nnsp.2002.1030033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nnsp.2002.1030033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing","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/A5083261801","display_name":"Deniz Erdo\u011fmu\u015f","orcid":"https://orcid.org/0000-0002-1114-3539"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"D. Erdogmus","raw_affiliation_strings":["Computational NeuroEngineering Laboratory, Electrical & Computer Engineering Department, University of Florida, Gainesville, FL, USA","Dept. of Electr. & Comput. Eng.,, Florida Univ., Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"Computational NeuroEngineering Laboratory, Electrical & Computer Engineering Department, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng.,, Florida Univ., Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090559862","display_name":"Justin C. Sanchez","orcid":"https://orcid.org/0000-0002-2094-8400"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J.C. Sanchez","raw_affiliation_strings":["Biomedical Engineering Department, University of Florida, Gainesville, FL, USA","[University of Florida]"],"affiliations":[{"raw_affiliation_string":"Biomedical Engineering Department, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"[University of Florida]","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019504861","display_name":"Jos\u00e9 C. Pr\u0131\u0301ncipe","orcid":"https://orcid.org/0000-0002-3449-3531"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J.C. Principe","raw_affiliation_strings":["Computational NeuroEngineering Laboratory, Electrical & Computer Engineering Department, University of Florida, Gainesville, FL, USA","[University of Florida]"],"affiliations":[{"raw_affiliation_string":"Computational NeuroEngineering Laboratory, Electrical & Computer Engineering Department, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"[University of Florida]","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5083261801"],"corresponding_institution_ids":["https://openalex.org/I33213144"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.13402723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"219","last_page":"228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9991000294685364,"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":0.9977999925613403,"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/backpropagation","display_name":"Backpropagation","score":0.7587605118751526},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.698628306388855},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.61992347240448},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5948601961135864},{"id":"https://openalex.org/keywords/jacobian-matrix-and-determinant","display_name":"Jacobian matrix and determinant","score":0.58949875831604},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5870406031608582},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.5775607228279114},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5213421583175659},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4984602928161621},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.49595651030540466},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.45298251509666443},{"id":"https://openalex.org/keywords/ensemble-kalman-filter","display_name":"Ensemble Kalman filter","score":0.45062923431396484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42507821321487427},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20954567193984985}],"concepts":[{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.7587605118751526},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.698628306388855},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.61992347240448},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5948601961135864},{"id":"https://openalex.org/C200331156","wikidata":"https://www.wikidata.org/wiki/Q506041","display_name":"Jacobian matrix and determinant","level":2,"score":0.58949875831604},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5870406031608582},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.5775607228279114},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5213421583175659},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4984602928161621},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.49595651030540466},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.45298251509666443},{"id":"https://openalex.org/C79334102","wikidata":"https://www.wikidata.org/wiki/Q3072268","display_name":"Ensemble Kalman filter","level":4,"score":0.45062923431396484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42507821321487427},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20954567193984985},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/nnsp.2002.1030033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nnsp.2002.1030033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing","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":13,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1554663460","https://openalex.org/W2020934227","https://openalex.org/W2107878631","https://openalex.org/W2112462566","https://openalex.org/W2123716044","https://openalex.org/W2124776405","https://openalex.org/W2132152975","https://openalex.org/W2150355110","https://openalex.org/W3217625971","https://openalex.org/W4299507991","https://openalex.org/W6655473528","https://openalex.org/W6676789009"],"related_works":["https://openalex.org/W2007405763","https://openalex.org/W3136087161","https://openalex.org/W1486373823","https://openalex.org/W2119578520","https://openalex.org/W2053762185","https://openalex.org/W2913611334","https://openalex.org/W1984283682","https://openalex.org/W1965257389","https://openalex.org/W2018238589","https://openalex.org/W2145980196"],"abstract_inverted_index":{"Kalman":[0,59],"filter":[1,60],"based":[2],"training":[3,63],"algorithms":[4,21],"for":[5,62],"recurrent":[6,36,64],"neural":[7,65],"networks":[8],"provide":[9],"a":[10,56],"clever":[11],"alternative":[12],"to":[13,50],"the":[14,27,30,35,46,76,85,99,105],"standard":[15],"backpropagation":[16,94],"in":[17],"time.":[18],"However,":[19],"these":[20],"do":[22],"not":[23],"take":[24],"into":[25],"account":[26],"optimization":[28],"of":[29,34,79,87,104],"hidden":[31],"state":[32],"variables":[33],"network.":[37],"In":[38],"addition,":[39],"their":[40,51],"formulation":[41,73],"requires":[42],"Jacobian":[43,80],"evaluations":[44,81],"over":[45],"entire":[47],"network,":[48],"adding":[49],"computational":[52,77],"complexity.":[53],"We":[54],"propose":[55],"spatial-temporal":[57],"extended":[58],"algorithm":[61],"network":[66],"weights":[67],"and":[68,101],"internal":[69],"states.":[70],"This":[71],"new":[72],"also":[74],"reduces":[75],"complexity":[78],"drastically":[82],"by":[83],"decoupling":[84],"gradients":[86],"each":[88],"layer.":[89],"Monte":[90],"Carlo":[91],"comparisons":[92],"with":[93],"through":[95],"time":[96],"point":[97],"out":[98],"robust":[100],"fast":[102],"convergence":[103],"algorithm.":[106]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
