{"id":"https://openalex.org/W3005515502","doi":"https://doi.org/10.1109/lsp.2020.2972164","title":"Kernel Recursive Least Squares Algorithm Based on the Nystr${\\rm {{\\ddot{\\bf {o}}}}}$m Method With $k$-Means Sampling","display_name":"Kernel Recursive Least Squares Algorithm Based on the Nystr${\\rm {{\\ddot{\\bf {o}}}}}$m Method With $k$-Means Sampling","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3005515502","doi":"https://doi.org/10.1109/lsp.2020.2972164","mag":"3005515502"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2020.2972164","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.2972164","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5103057449","display_name":"Tao Zhang","orcid":"https://orcid.org/0000-0001-9130-3848"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Zhang","raw_affiliation_strings":["College of Electronic and Information Engineering, the Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, the Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100640301","display_name":"Shiyuan Wang","orcid":"https://orcid.org/0000-0002-5028-5839"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiyuan Wang","raw_affiliation_strings":["College of Electronic and Information Engineering, the Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, the Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045292855","display_name":"Xuewei Huang","orcid":"https://orcid.org/0000-0001-9189-5556"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuewei Huang","raw_affiliation_strings":["College of Electronic and Information Engineering, the Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, the Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101093032","display_name":"Lei Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Jia","raw_affiliation_strings":["College of Electronic and Information Engineering, the Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, the Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103057449"],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":null,"apc_paid":null,"fwci":1.5845,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.79679408,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"27","issue":null,"first_page":"361","last_page":"365"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9986000061035156,"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/kernel","display_name":"Kernel (algebra)","score":0.7279775142669678},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6499522924423218},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.5211270451545715},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5075916051864624},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4701029658317566},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.4691423773765564},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4594835042953491},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.43505728244781494},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4031776189804077},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.195295512676239},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.1740642488002777},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17318779230117798},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.08516797423362732}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7279775142669678},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6499522924423218},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.5211270451545715},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5075916051864624},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4701029658317566},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.4691423773765564},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4594835042953491},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.43505728244781494},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4031776189804077},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.195295512676239},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.1740642488002777},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17318779230117798},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.08516797423362732},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2020.2972164","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.2972164","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1357542713","display_name":null,"funder_award_id":"XDJK2019C018","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G2189274656","display_name":null,"funder_award_id":"61671389","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7279913291","display_name":null,"funder_award_id":"XDJK2019B011","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1578320724","https://openalex.org/W1819447595","https://openalex.org/W1882844461","https://openalex.org/W2011197824","https://openalex.org/W2012915481","https://openalex.org/W2021231414","https://openalex.org/W2030504178","https://openalex.org/W2071820974","https://openalex.org/W2075336646","https://openalex.org/W2107791152","https://openalex.org/W2112545207","https://openalex.org/W2114865067","https://openalex.org/W2125525099","https://openalex.org/W2126709692","https://openalex.org/W2141566892","https://openalex.org/W2150621701","https://openalex.org/W2153290280","https://openalex.org/W2160840682","https://openalex.org/W2186379922","https://openalex.org/W2481926318","https://openalex.org/W2734874104","https://openalex.org/W2756387736","https://openalex.org/W2801725476","https://openalex.org/W2899745586","https://openalex.org/W2905386110","https://openalex.org/W2972958113"],"related_works":["https://openalex.org/W4385609682","https://openalex.org/W2913271688","https://openalex.org/W2118190631","https://openalex.org/W2130314481","https://openalex.org/W2913715341","https://openalex.org/W2963926425","https://openalex.org/W3132366479","https://openalex.org/W2990107052","https://openalex.org/W1493568480","https://openalex.org/W2899532525"],"abstract_inverted_index":{"The":[0],"kernel":[1,18,51,63,81],"recursive":[2,52,82],"least":[3,53,83],"squares":[4,54,84],"(KRLS)":[5],"algorithm":[6,56,89,146],"is":[7,57,73],"used":[8],"to":[9,77],"improve":[10],"the":[11,23,28,61,65,70,93,109,113,121,140,143,148],"convergence":[12],"rate":[13],"and":[14,41,119,134,152],"filtering":[15],"accuracy":[16],"of":[17,39,136,142,150],"adaptive":[19],"filters":[20],"(KAFs)":[21],"in":[22,33,75],"Gaussian":[24,62],"noise":[25],"case.":[26],"However,":[27],"linear":[29],"growing":[30],"network":[31,101],"size":[32],"KRLS":[34,125],"poses":[35],"a":[36,48,98],"huge":[37],"amount":[38],"time":[40],"storage":[42],"consumption.":[43],"To":[44],"address":[45],"this":[46],"issue,":[47],"novel":[49],"Nystr\u00f6m":[50,66,80],"(NysKRLS)":[55],"proposed":[58,144],"by":[59],"approximating":[60],"with":[64,85,97],"method.":[67],"In":[68],"addition,":[69],"k-means":[71,86],"sampling":[72,87],"adopted":[74],"NysKRLS":[76],"develop":[78],"another":[79],"(NysKRLS-KM)":[88],"for":[90],"further":[91],"improving":[92],"approximation":[94],"accuracy.":[95],"NysKRLS-KM":[96,145],"fixed":[99],"dimensional":[100],"structure":[102],"can":[103],"achieve":[104],"significantly":[105],"better":[106],"performance":[107,123],"than":[108],"KAFs":[110],"based":[111],"on":[112,130],"stochastic":[114],"gradient":[115],"descent":[116],"(SGD)":[117],"method,":[118],"almost":[120],"same":[122],"as":[124],"efficiently.":[126],"Monte":[127],"Carlo":[128],"simulations":[129],"nonlinear":[131],"system":[132],"identification":[133],"prediction":[135],"real-world":[137],"data":[138],"illustrate":[139],"superiorities":[141],"from":[147],"aspects":[149],"computational":[151],"spatial":[153],"complexity.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
