{"id":"https://openalex.org/W3127442824","doi":"https://doi.org/10.1155/2021/8840757","title":"Calibration for Parameter Estimation of Signals with Complex Noise via Nonstationarity Measure","display_name":"Calibration for Parameter Estimation of Signals with Complex Noise via Nonstationarity Measure","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3127442824","doi":"https://doi.org/10.1155/2021/8840757","mag":"3127442824"},"language":"en","primary_location":{"id":"doi:10.1155/2021/8840757","is_oa":true,"landing_page_url":"http://doi.org/10.1155/2021/8840757","pdf_url":"https://downloads.hindawi.com/journals/complexity/2021/8840757.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://downloads.hindawi.com/journals/complexity/2021/8840757.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000546663","display_name":"Zhiming Zhou","orcid":"https://orcid.org/0000-0002-0851-3930"},"institutions":[{"id":"https://openalex.org/I111950717","display_name":"Macau University of Science and Technology","ror":"https://ror.org/03jqs2n27","country_code":"MO","type":"education","lineage":["https://openalex.org/I111950717","https://openalex.org/I4391767947"]},{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN","MO"],"is_corresponding":false,"raw_author_name":"Zhiming Zhou","raw_affiliation_strings":["Center for Mathematical Sciences and Department of Mathematics, Wuhan University of Technology, Wuhan 430070, China","The Faculty of Information Technology, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Mathematical Sciences and Department of Mathematics, Wuhan University of Technology, Wuhan 430070, China","institution_ids":["https://openalex.org/I196699116"]},{"raw_affiliation_string":"The Faculty of Information Technology, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China","institution_ids":["https://openalex.org/I111950717"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111901693","display_name":"Zhengyun Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyun Zhou","raw_affiliation_strings":["Center for Mathematical Sciences and Department of Mathematics, Wuhan University of Technology, Wuhan 430070, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Mathematical Sciences and Department of Mathematics, Wuhan University of Technology, Wuhan 430070, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018762158","display_name":"Liang Wu","orcid":"https://orcid.org/0000-0002-7210-9107"},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liang Wu","raw_affiliation_strings":["Center of Statistical Research, School of Statistics, Southwestern University of Finance and Economics, Chengdu 611130, China"],"raw_orcid":"https://orcid.org/0000-0002-7210-9107","affiliations":[{"raw_affiliation_string":"Center of Statistical Research, School of Statistics, Southwestern University of Finance and Economics, Chengdu 611130, China","institution_ids":["https://openalex.org/I204831749"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5018762158"],"corresponding_institution_ids":["https://openalex.org/I204831749"],"apc_list":{"value":2300,"currency":"USD","value_usd":2300},"apc_paid":{"value":2300,"currency":"USD","value_usd":2300},"fwci":0.6603,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60611179,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"2021","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13487","display_name":"Statistical and numerical algorithms","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13487","display_name":"Statistical and numerical algorithms","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9757000207901001,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9693999886512756,"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/noise","display_name":"Noise (video)","score":0.7532525658607483},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6538913249969482},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.6272916793823242},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5973750948905945},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.5945940017700195},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5446069836616516},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.5317700505256653},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.5141127705574036},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.507553219795227},{"id":"https://openalex.org/keywords/gradient-noise","display_name":"Gradient noise","score":0.4741503596305847},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.4364798963069916},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4332778751850128},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.4189717769622803},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.41780516505241394},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3747323751449585},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3658845126628876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2036643624305725},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.19127321243286133},{"id":"https://openalex.org/keywords/noise-floor","display_name":"Noise floor","score":0.13485047221183777},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.11541199684143066},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.08922532200813293},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07321852445602417}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7532525658607483},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6538913249969482},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.6272916793823242},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5973750948905945},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.5945940017700195},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5446069836616516},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.5317700505256653},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.5141127705574036},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.507553219795227},{"id":"https://openalex.org/C200378446","wikidata":"https://www.wikidata.org/wiki/Q4147391","display_name":"Gradient noise","level":5,"score":0.4741503596305847},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.4364798963069916},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4332778751850128},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.4189717769622803},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.41780516505241394},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3747323751449585},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3658845126628876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2036643624305725},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.19127321243286133},{"id":"https://openalex.org/C187612029","wikidata":"https://www.wikidata.org/wiki/Q17083130","display_name":"Noise floor","level":4,"score":0.13485047221183777},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.11541199684143066},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.08922532200813293},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07321852445602417},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1155/2021/8840757","is_oa":true,"landing_page_url":"http://doi.org/10.1155/2021/8840757","pdf_url":"https://downloads.hindawi.com/journals/complexity/2021/8840757.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:hin:complx:8840757","is_oa":false,"landing_page_url":"http://downloads.hindawi.com/journals/complexity/2021/8840757.xml","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:4ce58a0ffe5c4ca2ae100bc259ab0f03","is_oa":true,"landing_page_url":"https://doaj.org/article/4ce58a0ffe5c4ca2ae100bc259ab0f03","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Complexity, Vol 2021 (2021)","raw_type":"article"},{"id":"pmh:oai:hindawi.com:10.1155/2021/8840757","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/8840757","pdf_url":null,"source":{"id":"https://openalex.org/S4306400340","display_name":"Hindawi Journal of Chemistry (Hindawi)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210126990","host_organization_name":"Hindawi (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210126990"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Research Article"}],"best_oa_location":{"id":"doi:10.1155/2021/8840757","is_oa":true,"landing_page_url":"http://doi.org/10.1155/2021/8840757","pdf_url":"https://downloads.hindawi.com/journals/complexity/2021/8840757.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7986496254","display_name":null,"funder_award_id":"JBK1806002","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3127442824.pdf","grobid_xml":"https://content.openalex.org/works/W3127442824.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1528589873","https://openalex.org/W2005307031","https://openalex.org/W2014760270","https://openalex.org/W2038623285","https://openalex.org/W2070284886","https://openalex.org/W2087070363","https://openalex.org/W2170936677","https://openalex.org/W2236623899","https://openalex.org/W2256578114","https://openalex.org/W2343539894","https://openalex.org/W2529901948","https://openalex.org/W2899674823","https://openalex.org/W2933266832","https://openalex.org/W2984447777","https://openalex.org/W3003812244","https://openalex.org/W3004690961","https://openalex.org/W3012546083","https://openalex.org/W3014314278","https://openalex.org/W3035279979","https://openalex.org/W3035784675","https://openalex.org/W3037032721"],"related_works":["https://openalex.org/W2588855097","https://openalex.org/W2955414824","https://openalex.org/W2092661960","https://openalex.org/W2161471497","https://openalex.org/W2811019791","https://openalex.org/W1986743941","https://openalex.org/W2949211747","https://openalex.org/W3178345791","https://openalex.org/W2052452674","https://openalex.org/W2135434361"],"abstract_inverted_index":{"The":[0,28],"signals":[1,22,39],"in":[2,38,75],"numerous":[3],"complex":[4,56],"systems":[5],"of":[6,35,78,87,90,101,133,166],"engineering":[7],"can":[8,47,128],"be":[9,160],"regarded":[10],"as":[11,58],"nonlinear":[12,36],"parameter":[13,33,80,154,168],"trend":[14,37],"with":[15,115],"noise":[16,54,117,123],"which":[17],"is":[18,55,142,150],"identically":[19],"distributed":[20],"random":[21,122],"or":[23],"deterministic":[24],"stationary":[25],"chaotic":[26,64,125],"signals.":[27],"commonly":[29],"used":[30],"methods":[31],"for":[32,72,98,112,163],"estimation":[34,50],"are":[40,96],"mainly":[41],"based":[42],"on":[43],"least":[44,138],"squares.":[45],"It":[46],"cause":[48],"inaccurate":[49],"results":[51,158],"when":[52],"the":[53,76,85,88,106,131,143,147,153],"(such":[57],"non\u2010Gaussian":[59],"noise,":[60,62],"strong":[61],"and":[63,119,124,127],"noise).":[65],"This":[66,141],"paper":[67],"proposes":[68],"a":[69,161],"calibration":[70,108],"method":[71,109],"this":[73],"issue":[74],"case":[77],"single":[79],"via":[81],"nonstationarity":[82,148],"measure":[83,149],"from":[84],"perspective":[86],"stationarity":[89],"residual":[91],"sequence.":[92],"Some":[93],"numerical":[94,102],"studies":[95,103,165],"conducted":[97],"validation.":[99],"Results":[100],"show":[104],"that":[105,146],"proposed":[107],"performs":[110],"well":[111],"various":[113],"models":[114],"different":[116],"strengths":[118],"types":[120],"(including":[121],"noise)":[126],"significantly":[129],"improve":[130],"accuracy":[132],"initial":[134],"estimates":[135],"obtained":[136],"by":[137],"squares":[139],"method.":[140],"first":[144],"time":[145],"applied":[151],"to":[152],"calibration.":[155],"All":[156],"these":[157],"will":[159],"guide":[162],"future":[164],"other":[167],"calibrations.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}