{"id":"https://openalex.org/W4312298574","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892032","title":"Kernel Nonlinear Dynamic System Identification Based on Expectation-Maximization Method","display_name":"Kernel Nonlinear Dynamic System Identification Based on Expectation-Maximization Method","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312298574","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892032"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892032","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892032","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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/A5090275826","display_name":"Pingping Zhu","orcid":"https://orcid.org/0000-0002-9045-2398"},"institutions":[{"id":"https://openalex.org/I88694374","display_name":"Marshall University","ror":"https://ror.org/02erqft81","country_code":"US","type":"education","lineage":["https://openalex.org/I88694374"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pingping Zhu","raw_affiliation_strings":["Marshall University,Dept. of Computer Science and Electrical Engineering,Huntington,USA","Dept. of Computer Science and Electrical Engineering, Marshall University, Huntington, USA"],"affiliations":[{"raw_affiliation_string":"Marshall University,Dept. of Computer Science and Electrical Engineering,Huntington,USA","institution_ids":["https://openalex.org/I88694374"]},{"raw_affiliation_string":"Dept. of Computer Science and Electrical Engineering, Marshall University, Huntington, USA","institution_ids":["https://openalex.org/I88694374"]}]},{"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":"Jose C. Principe","raw_affiliation_strings":["University of Florida,Dept. of Electrical and Computer Engineering,Gainesville,USA","Dept. of Electrical and Computer Engineering, University of Florida, Gainesville, USA"],"affiliations":[{"raw_affiliation_string":"University of Florida,Dept. of Electrical and Computer Engineering,Gainesville,USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, University of Florida, Gainesville, USA","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5090275826"],"corresponding_institution_ids":["https://openalex.org/I88694374"],"apc_list":null,"apc_paid":null,"fwci":0.3539,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.47360971,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9980999827384949,"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":0.9980999827384949,"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/T10320","display_name":"Neural Networks and Applications","score":0.9965999722480774,"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":0.9959999918937683,"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/reproducing-kernel-hilbert-space","display_name":"Reproducing kernel Hilbert space","score":0.6756105422973633},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6426149606704712},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.607513964176178},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5388540625572205},{"id":"https://openalex.org/keywords/system-identification","display_name":"System identification","score":0.49131765961647034},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4891660511493683},{"id":"https://openalex.org/keywords/hilbert-space","display_name":"Hilbert space","score":0.46414437890052795},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.4609236717224121},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.45909982919692993},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4398559033870697},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.4387800395488739},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.41842329502105713},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4171483516693115},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4115992784500122},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.41155123710632324},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38864749670028687},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24918344616889954},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.22233504056930542},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.08971935510635376},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08210167288780212}],"concepts":[{"id":"https://openalex.org/C80884492","wikidata":"https://www.wikidata.org/wiki/Q3345678","display_name":"Reproducing kernel Hilbert space","level":3,"score":0.6756105422973633},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6426149606704712},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.607513964176178},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5388540625572205},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.49131765961647034},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4891660511493683},{"id":"https://openalex.org/C62799726","wikidata":"https://www.wikidata.org/wiki/Q190056","display_name":"Hilbert space","level":2,"score":0.46414437890052795},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.4609236717224121},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.45909982919692993},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4398559033870697},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.4387800395488739},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.41842329502105713},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4171483516693115},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4115992784500122},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41155123710632324},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38864749670028687},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24918344616889954},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.22233504056930542},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.08971935510635376},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08210167288780212},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892032","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892032","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6758477350","display_name":null,"funder_award_id":"W911NF-21-1-0254","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1581808154","https://openalex.org/W1598493736","https://openalex.org/W1749494163","https://openalex.org/W1756404937","https://openalex.org/W1963718895","https://openalex.org/W1977606287","https://openalex.org/W2011197824","https://openalex.org/W2013742732","https://openalex.org/W2025970272","https://openalex.org/W2026108168","https://openalex.org/W2029066446","https://openalex.org/W2049650637","https://openalex.org/W2053449276","https://openalex.org/W2054091988","https://openalex.org/W2071820974","https://openalex.org/W2082068808","https://openalex.org/W2092766760","https://openalex.org/W2094227853","https://openalex.org/W2098613108","https://openalex.org/W2104849640","https://openalex.org/W2114813823","https://openalex.org/W2123487311","https://openalex.org/W2126423185","https://openalex.org/W2137043637","https://openalex.org/W2147929628","https://openalex.org/W2166417161","https://openalex.org/W2168452625","https://openalex.org/W2210387432","https://openalex.org/W3111424697","https://openalex.org/W4206129260","https://openalex.org/W6681655254"],"related_works":["https://openalex.org/W4293053089","https://openalex.org/W4322759964","https://openalex.org/W4362684611","https://openalex.org/W1558422751","https://openalex.org/W2095593773","https://openalex.org/W2320819545","https://openalex.org/W2333984532","https://openalex.org/W183296071","https://openalex.org/W2392804273","https://openalex.org/W2172005334"],"abstract_inverted_index":{"This":[0],"paper":[1],"develops":[2],"a":[3],"kernel":[4,32,61,76],"nonlinear":[5,77],"system":[6,78,98,101,127,150],"identification":[7,79],"approach":[8,133,139],"to":[9,83,120,154],"dual":[10,53],"estimation":[11],"problems.":[12],"Given":[13],"the":[14,18,22,30,37,45,52,55,59,70,75,84,89,94,108,121,125,130,137,143,148],"observation":[15,20],"model":[16,151],"and":[17,117,140],"corresponding":[19,38],"sequence,":[21],"unknown":[23,100],"state":[24],"transition":[25],"function":[26,65],"is":[27,66,81,114,118,134,152],"approximated":[28,67],"in":[29],"reproducing":[31],"Hilbert":[33],"space":[34],"(RKHS),":[35],"while":[36],"hidden":[39],"states":[40],"are":[41,91],"also":[42],"estimated":[43],"with":[44,99,124,136],"unscented":[46,71],"Kalman":[47],"smoother":[48],"(UKS).":[49],"To":[50],"implement":[51],"estimation,":[54,87],"optimization":[56],"solution":[57],"of":[58],"proposed":[60,131],"expectation-maximization":[62],"(EM)":[63],"cost":[64],"based":[68],"on":[69],"transform":[72],"(UT).":[73],"Finally,":[74],"method":[80],"applied":[82],"noisy":[85,109],"time-series":[86],"where":[88],"data":[90],"generated":[92],"by":[93],"IKEDA":[95],"chaotic":[96],"dynamical":[97],"parameters.":[102],"The":[103],"simulation":[104],"results":[105],"show":[106],"that":[107],"data's":[110],"signal-noise":[111],"ratio":[112],"(SNR)":[113],"improved":[115],"significantly":[116],"close":[119],"SNR":[122],"obtained":[123],"accurate":[126],"model.":[128],"Furthermore,":[129],"non-parametric":[132],"compared":[135],"parametric":[138,144],"outperforms":[141],"obviously":[142],"approach,":[145],"even":[146],"if":[147],"parameterized":[149],"assumed":[153],"be":[155],"known.":[156]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}