{"id":"https://openalex.org/W2092535535","doi":"https://doi.org/10.1080/0020772031000115542","title":"Comparison of four gradient-learning algorithms for neural network Wiener models","display_name":"Comparison of four gradient-learning algorithms for neural network Wiener models","publication_year":2003,"publication_date":"2003-01-01","ids":{"openalex":"https://openalex.org/W2092535535","doi":"https://doi.org/10.1080/0020772031000115542","mag":"2092535535"},"language":"en","primary_location":{"id":"doi:10.1080/0020772031000115542","is_oa":false,"landing_page_url":"https://doi.org/10.1080/0020772031000115542","pdf_url":null,"source":{"id":"https://openalex.org/S129640837","display_name":"International Journal of Systems Science","issn_l":"0020-7721","issn":["0020-7721","1464-5319"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Systems Science","raw_type":"journal-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/A5066619455","display_name":"Andrzej Janczak","orcid":null},"institutions":[{"id":"https://openalex.org/I46305939","display_name":"University of Zielona G\u00f3ra","ror":"https://ror.org/04fzm7v55","country_code":"PL","type":"education","lineage":["https://openalex.org/I46305939"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Andrzej Janczak","raw_affiliation_strings":["Institute of Control and Computations Engineering , University of Zielona G\u00f3ra , Zielona G\u00f3ra, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Control and Computations Engineering , University of Zielona G\u00f3ra , Zielona G\u00f3ra, Poland","institution_ids":["https://openalex.org/I46305939"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5066619455"],"corresponding_institution_ids":["https://openalex.org/I46305939"],"apc_list":null,"apc_paid":null,"fwci":2.4451,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.89225596,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"34","issue":"1","first_page":"21","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9955999851226807,"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"}},"topics":[{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9955999851226807,"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"}},{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9926000237464905,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.8714823722839355},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7009515762329102},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.603473424911499},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.593369722366333},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.5266998410224915},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4714706242084503},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.47130855917930603},{"id":"https://openalex.org/keywords/gradient-method","display_name":"Gradient method","score":0.4476524591445923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3928796947002411}],"concepts":[{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.8714823722839355},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7009515762329102},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.603473424911499},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.593369722366333},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.5266998410224915},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4714706242084503},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.47130855917930603},{"id":"https://openalex.org/C115680565","wikidata":"https://www.wikidata.org/wiki/Q5977448","display_name":"Gradient method","level":2,"score":0.4476524591445923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3928796947002411},{"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/0020772031000115542","is_oa":false,"landing_page_url":"https://doi.org/10.1080/0020772031000115542","pdf_url":null,"source":{"id":"https://openalex.org/S129640837","display_name":"International Journal of Systems Science","issn_l":"0020-7721","issn":["0020-7721","1464-5319"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Systems Science","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3123071383","https://openalex.org/W3170244987","https://openalex.org/W2391384657","https://openalex.org/W3159389381","https://openalex.org/W4295266589","https://openalex.org/W2570846706","https://openalex.org/W2034060070","https://openalex.org/W1900101064","https://openalex.org/W2148725422","https://openalex.org/W2390166185"],"abstract_inverted_index":{"A":[0,129],"gradient-based":[1],"approach":[2],"to":[3,96,146],"training":[4],"neural":[5,100],"network":[6,101],"Wiener":[7,23,109],"models":[8,24,110],"is":[9,38,59],"presented.":[10],"Calculation":[11],"of":[12,64,67,77,82,86,90,104,138,149],"the":[13,19,26,28,33,55,62,65,75,87,97,105,112,127],"gradient":[14,17,106],"or":[15,115],"approximate":[16],"for":[18],"series-parallel":[20],"and":[21,32,52,133,152,155],"parallel":[22,108],"by":[25],"backpropagation,":[27],"sensitivity":[29,83,113],"method":[30,114],"(SM)":[31],"backpropagation":[34,116],"through":[35,117],"time":[36,69,118],"(BPTT)":[37],"considered":[39],"in":[40,107],"a":[41,121,134,139],"unified":[42],"framework.":[43],"Four":[44],"different":[45,150],"recursive":[46],"learning":[47],"algorithms":[48,92],"are":[49,143,158],"derived,":[50],"analysed":[51],"compared.":[53],"For":[54],"truncated":[56],"BPTT,":[57],"it":[58],"shown":[60],"that":[61],"determination":[63],"number":[66],"unfolding":[68],"steps":[70],"can":[71],"be":[72],"made":[73],"on":[74],"basis":[76],"an":[78],"impulse":[79],"response":[80],"function":[81],"models.":[84],"Analysis":[85],"computational":[88,124],"complexity":[89],"these":[91],"shows":[93],"that,":[94],"contrary":[95],"other":[98],"recurrent":[99],"models,":[102],"computation":[103],"with":[111],"requires":[119],"only":[120],"little":[122],"more":[123],"burden":[125],"than":[126],"backpropagation.":[128],"simulated":[130],"data":[131,136],"example":[132,137],"real":[135],"laboratory":[140],"two-tank":[141],"system":[142],"also":[144],"included":[145],"make":[147],"comparison":[148],"methods":[151],"their":[153],"effectiveness":[154],"practical":[156],"feasibility":[157],"shown.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}