{"id":"https://openalex.org/W4414871363","doi":"https://doi.org/10.1109/tase.2025.3617969","title":"Activation Control of Laguerre Neural Network","display_name":"Activation Control of Laguerre Neural Network","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414871363","doi":"https://doi.org/10.1109/tase.2025.3617969"},"language":"en","primary_location":{"id":"doi:10.1109/tase.2025.3617969","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2025.3617969","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","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/A5059223640","display_name":"Chen Hou","orcid":"https://orcid.org/0000-0002-5273-0502"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Hou","raw_affiliation_strings":["National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5059223640"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14224294,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.972599983215332,"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":0.972599983215332,"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/laguerre-polynomials","display_name":"Laguerre polynomials","score":0.8330000042915344},{"id":"https://openalex.org/keywords/optimal-control","display_name":"Optimal control","score":0.6672000288963318},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5776000022888184},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5256999731063843},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.474700003862381},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.4108999967575073},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.3878999948501587},{"id":"https://openalex.org/keywords/approximation-theory","display_name":"Approximation theory","score":0.3400999903678894}],"concepts":[{"id":"https://openalex.org/C108408018","wikidata":"https://www.wikidata.org/wiki/Q1124546","display_name":"Laguerre polynomials","level":2,"score":0.8330000042915344},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.6672000288963318},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5776000022888184},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5595999956130981},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5256999731063843},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.474700003862381},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4564000070095062},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.4108999967575073},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.3878999948501587},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3418999910354614},{"id":"https://openalex.org/C145242015","wikidata":"https://www.wikidata.org/wiki/Q774123","display_name":"Approximation theory","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.3287999927997589},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.32280001044273376},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.29809999465942383},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.2809000015258789},{"id":"https://openalex.org/C46421273","wikidata":"https://www.wikidata.org/wiki/Q1407668","display_name":"Hopfield network","level":3,"score":0.27810001373291016},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.27390000224113464}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2025.3617969","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2025.3617969","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5403254464","display_name":null,"funder_award_id":"4252038","funder_id":"https://openalex.org/F4320334977","funder_display_name":"Beijing Municipal Natural Science Foundation"},{"id":"https://openalex.org/G6614757958","display_name":null,"funder_award_id":"62303472","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334977","display_name":"Beijing Municipal Natural Science Foundation","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"Laguerre":[1,6],"Neural":[2],"Network":[3],"(LaNN)":[4],"employs":[5],"polynomials":[7],"(LPs)":[8],"as":[9,92,120,130],"the":[10,20,25,29,34,41,47,56,76,82,112,116,121,124,128,131,135,148,168,172,175,199,203,210,221],"activation":[11,37,77,150],"functions":[12,22,38],"of":[13,27,40,78,114,127,138,170,178,201,213,229],"its":[14,186,230],"hidden":[15],"neurons":[16],"(HNs)":[17],"to":[18,60,69,74,80,166,207],"approximate":[19],"nonlinear":[21],"(NFs).":[23],"From":[24],"perspective":[26],"statistics,":[28],"more":[30,35,61],"LPs":[31,79],"are":[32],"activated,":[33],"LP-based":[36],"(LPAFs)":[39],"HNs":[42,139],"will":[43,52],"operate,":[44],"and":[45,88,140,145,188,233],"thus":[46,141],"smaller":[48],"approximation":[49,86,234],"error":[50],"(APE)":[51],"be":[53],"suffered":[54],"by":[55,205],"LaNN,":[57],"while":[58,123],"leading":[59],"energy":[62,89,125,179,231],"consumption":[63,90,126,180],"since":[64],"activating":[65],"any":[66],"LP":[67],"has":[68],"consume":[70],"energy.":[71,214],"Therefore,":[72],"how":[73],"control":[75],"make":[81],"optimal":[83,136,143,149],"tradeoff":[84],"between":[85],"accuracy":[87],"arises":[91],"an":[93,104],"interesting":[94],"issue.":[95],"To":[96,215],"address":[97],"this":[98,100,219],"issue,":[99],"paper":[101],"first":[102],"establishes":[103],"energy-constraint":[105],"probability-based":[106],"approximation-accuracy":[107],"optimization-theoretical":[108],"(EPAO)":[109],"framework,":[110],"considering":[111],"probability":[113,151,169,200],"obtaining":[115,171,202],"minimum":[117],"APE":[118],"(MAPE)":[119],"objective":[122],"LaNN":[129,165,225],"constraint,":[132],"then":[133],"reveals":[134],"number":[137],"their":[142],"LPAFs,":[144],"finally":[146],"discloses":[147],"for":[152,164,224],"each":[153],"LP.":[154],"Based":[155],"on":[156],"our":[157,216],"discovered":[158],"theoretical":[159],"results,":[160],"a":[161],"novel":[162],"algorithm":[163],"maximize":[167],"MAPE":[173,204],"at":[174,209],"acceptable":[176],"level":[177],"is":[181,220],"proposed.":[182],"Theoretical":[183],"analysis":[184],"verifies":[185],"performance,":[187],"field":[189],"experiments":[190],"verify":[191],"that,":[192],"compared":[193],"with":[194],"existing":[195],"methods,":[196],"it":[197],"improves":[198],"6.00%":[206],"20.26%":[208],"similar":[211],"cost":[212],"best":[217],"knowledge,":[218],"initial":[222],"work":[223],"towards":[226],"joint":[227],"optimization":[228],"efficiency":[232],"accuracy.":[235]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
