{"id":"https://openalex.org/W1997005159","doi":"https://doi.org/10.1002/(sici)1097-007x(199903/04)27:2<209::aid-cta54>3.0.co;2-7","title":"Learning in dynamic neural networks using signal flow graphs","display_name":"Learning in dynamic neural networks using signal flow graphs","publication_year":1999,"publication_date":"1999-03-01","ids":{"openalex":"https://openalex.org/W1997005159","doi":"https://doi.org/10.1002/(sici)1097-007x(199903/04)27:2<209::aid-cta54>3.0.co;2-7","mag":"1997005159"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1002/(sici)1097-007x(199903/04)27:2<209::aid-cta54>3.0.co;2-7","pdf_url":null,"source":{"id":"https://openalex.org/S92132303","display_name":"International Journal of Circuit Theory and Applications","issn_l":"0098-9886","issn":["0098-9886","1097-007X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5009405646","display_name":"S. Osowski","orcid":"https://orcid.org/0000-0003-3194-4656"},"institutions":[{"id":"https://openalex.org/I108403487","display_name":"Warsaw University of Technology","ror":"https://ror.org/00y0xnp53","country_code":"PL","type":"education","lineage":["https://openalex.org/I108403487"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Stanislaw Osowski","raw_affiliation_strings":["Institute of the Theory of Electrical Engineering and Electrical Measurements, Warsaw University of Technology, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"Institute of the Theory of Electrical Engineering and Electrical Measurements, Warsaw University of Technology, Warsaw, Poland","institution_ids":["https://openalex.org/I108403487"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018676117","display_name":"Andrzej Cichocki","orcid":"https://orcid.org/0000-0002-8364-7226"},"institutions":[{"id":"https://openalex.org/I108403487","display_name":"Warsaw University of Technology","ror":"https://ror.org/00y0xnp53","country_code":"PL","type":"education","lineage":["https://openalex.org/I108403487"]},{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]},{"id":"https://openalex.org/I4210110652","display_name":"RIKEN","ror":"https://ror.org/01sjwvz98","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652"]}],"countries":["JP","PL"],"is_corresponding":false,"raw_author_name":"Andrzej Cichocki","raw_affiliation_strings":["FRP RIKEN, Institute of Physical and Chemical Research Laboratory of Artificial Brain Systems, Hirosawa 2-1 Saitama, Wako-schi, Japan","Institute of the Theory of Electrical Engineering and Electrical Measurements, Warsaw University of Technology, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"Institute of the Theory of Electrical Engineering and Electrical Measurements, Warsaw University of Technology, Warsaw, Poland","institution_ids":["https://openalex.org/I108403487"]},{"raw_affiliation_string":"FRP RIKEN, Institute of Physical and Chemical Research Laboratory of Artificial Brain Systems, Hirosawa 2-1 Saitama, Wako-schi, Japan","institution_ids":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5009405646"],"corresponding_institution_ids":["https://openalex.org/I108403487"],"apc_list":{"value":3660,"currency":"USD","value_usd":3660,"provenance":"doaj"},"apc_paid":null,"fwci":0.0,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":3,"citation_normalized_percentile":{"value":0.60429,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":67,"max":70},"biblio":{"volume":"27","issue":"2","first_page":"209","last_page":"228"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9997,"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":0.9997,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.99,"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/T11236","display_name":"Control Systems and Identification","score":0.9869,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/signal-flow-graph","display_name":"Signal-flow graph","score":0.61874306},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5529575},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4413492}],"concepts":[{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.7373568},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6793075},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.63108224},{"id":"https://openalex.org/C166501922","wikidata":"https://www.wikidata.org/wiki/Q1786523","display_name":"Signal-flow graph","level":2,"score":0.61874306},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5529575},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.541638},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.5283832},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.50088024},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4966882},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.47979906},{"id":"https://openalex.org/C177973122","wikidata":"https://www.wikidata.org/wiki/Q7860946","display_name":"Types of artificial neural networks","level":4,"score":0.47400436},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4413492},{"id":"https://openalex.org/C134342201","wikidata":"https://www.wikidata.org/wiki/Q7246859","display_name":"Probabilistic neural network","level":4,"score":0.42713067},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35479605},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.24339},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10071251},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1002/(sici)1097-007x(199903/04)27:2<209::aid-cta54>3.0.co;2-7","pdf_url":null,"source":{"id":"https://openalex.org/S92132303","display_name":"International Journal of Circuit Theory and Applications","issn_l":"0098-9886","issn":["0098-9886","1097-007X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":18,"referenced_works":["https://openalex.org/W1548102932","https://openalex.org/W1562895369","https://openalex.org/W2016589492","https://openalex.org/W2038128936","https://openalex.org/W2063696533","https://openalex.org/W2072096856","https://openalex.org/W2081050493","https://openalex.org/W2114766824","https://openalex.org/W2114959414","https://openalex.org/W2115072676","https://openalex.org/W2124776405","https://openalex.org/W2132335233","https://openalex.org/W2138484437","https://openalex.org/W2145085734","https://openalex.org/W285212305","https://openalex.org/W2896916590","https://openalex.org/W291003596","https://openalex.org/W624148300"],"related_works":["https://openalex.org/W651238688","https://openalex.org/W4385506173","https://openalex.org/W4383737268","https://openalex.org/W2950917560","https://openalex.org/W2950022897","https://openalex.org/W2440925417","https://openalex.org/W2408618716","https://openalex.org/W2117224126","https://openalex.org/W1595652908","https://openalex.org/W149320829"],"abstract_inverted_index":{"The":[0,26,44,109],"paper":[1,57],"presents":[2],"the":[3,7,10,31,66,79,81,87,100,129,135],"universal":[4],"approach":[5,133],"to":[6,42,49,134],"determination":[8,113],"of":[9,23,33,65,70,90,111,120,125,131,138],"sensitivity":[11,112],"functions":[12],"for":[13],"dynamic":[14,71,83,91,101],"neural":[15,62,72,121,140],"networks":[16,73,141],"and":[17,37,76,105,145],"its":[18],"application":[19,32,130],"in":[20,78,117],"learning":[21,119,136],"algorithms":[22],"adaptive":[24],"networks.":[25,122],"method":[27,45],"is":[28,46,58],"based":[29],"on":[30],"signal":[34],"flow":[35],"graph":[36,40],"specially":[38],"defined":[39],"adjoint":[41],"it.":[43],"equally":[47],"applied":[48,116],"either":[50],"feed-forward":[51],"or":[52],"recurrent":[53,98,102,107,139],"network":[54,63,104],"structures.":[55],"This":[56],"mainly":[59],"concerned":[60],"with":[61],"applications":[64],"approach.":[67],"Different":[68],"kinds":[69],"are":[74,142],"considered":[75],"discussed":[77],"paper:":[80],"FIR":[82],"multilayer":[84],"perceptron":[85],"(MLP),":[86],"cascade":[88],"connection":[89],"MLPs":[92],"as":[93,95],"well":[94],"two":[96],"non-linear":[97],"systems:":[99],"MLP":[103],"ARMA":[106],"network.":[108],"rule":[110],"has":[114],"been":[115],"practical":[118],"Chosen":[123],"results":[124],"numerical":[126],"experiments":[127],"concerning":[128],"this":[132],"processes":[137],"also":[143],"given":[144],"discussed.":[146],"Copyright":[147],"\u00a9":[148],"1999":[149],"John":[150],"Wiley":[151],"&":[152],"Sons,":[153],"Ltd.":[154]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W1997005159","counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2024-12-17T13:21:58.264932","created_date":"2016-06-24"}