{"id":"https://openalex.org/W4220683809","doi":"https://doi.org/10.1080/03610918.2022.2047200","title":"A statistically efficient algorithm for estimating the parameters of a chirp signal model with time-varying amplitude","display_name":"A statistically efficient algorithm for estimating the parameters of a chirp signal model with time-varying amplitude","publication_year":2022,"publication_date":"2022-03-17","ids":{"openalex":"https://openalex.org/W4220683809","doi":"https://doi.org/10.1080/03610918.2022.2047200"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2022.2047200","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2047200","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","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/A5077814036","display_name":"Jiawen Bian","orcid":"https://orcid.org/0000-0002-2017-7845"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawen Bian","raw_affiliation_strings":["School of Mathematics and Physics, China University of Geosciences, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-2017-7845","affiliations":[{"raw_affiliation_string":"School of Mathematics and Physics, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100337906","display_name":"Zhihui Liu","orcid":"https://orcid.org/0000-0002-4232-7154"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihui Liu","raw_affiliation_strings":["School of Mathematics and Physics, China University of Geosciences, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-4232-7154","affiliations":[{"raw_affiliation_string":"School of Mathematics and Physics, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101934616","display_name":"Jing Xing","orcid":"https://orcid.org/0000-0003-3397-0655"},"institutions":[{"id":"https://openalex.org/I4210099437","display_name":"Hubei University Of Economics","ror":"https://ror.org/012a84b59","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099437"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Xing","raw_affiliation_strings":["Institute of Information Management and Statistics, Hubei University of Economics, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-3397-0655","affiliations":[{"raw_affiliation_string":"Institute of Information Management and Statistics, Hubei University of Economics, Wuhan, China","institution_ids":["https://openalex.org/I4210099437"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100325323","display_name":"Hongwei Li","orcid":"https://orcid.org/0000-0001-6809-7097"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongwei Li","raw_affiliation_strings":["Hubei Subsurface Multi-scale Imaging Key Laboratory, China University of Geosciences, Wuhan, China","School of Mathematics and Physics, China University of Geosciences, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hubei Subsurface Multi-scale Imaging Key Laboratory, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"School of Mathematics and Physics, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100325323"],"corresponding_institution_ids":["https://openalex.org/I3124059619"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01840761,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"53","issue":"3","first_page":"1423","last_page":"1443"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9980999827384949,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9980999827384949,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9969000220298767,"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/T11698","display_name":"Underwater Acoustics Research","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7158435583114624},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6693872213363647},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.601250171661377},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.5498303771018982},{"id":"https://openalex.org/keywords/chirp","display_name":"Chirp","score":0.5482197999954224},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5071578025817871},{"id":"https://openalex.org/keywords/amplitude","display_name":"Amplitude","score":0.47808170318603516},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.4689231514930725},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.46546128392219543},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4434608519077301},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.42596709728240967},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.39500176906585693},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.1612735390663147},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07400459051132202}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7158435583114624},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6693872213363647},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.601250171661377},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.5498303771018982},{"id":"https://openalex.org/C132794960","wikidata":"https://www.wikidata.org/wiki/Q27304","display_name":"Chirp","level":3,"score":0.5482197999954224},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5071578025817871},{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.47808170318603516},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.4689231514930725},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.46546128392219543},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4434608519077301},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.42596709728240967},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.39500176906585693},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.1612735390663147},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07400459051132202},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C520434653","wikidata":"https://www.wikidata.org/wiki/Q38867","display_name":"Laser","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2022.2047200","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2047200","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3639808319","display_name":"\u9762\u5411\u6cdb\u5728\u8ba1\u7b97\u7684\u7cbe\u51c6\u5ba4\u5185\u5bfc\u822a\u6280\u672f\u7814\u7a76","funder_award_id":"62072163","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8628149691","display_name":null,"funder_award_id":"61302138","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W655141528","https://openalex.org/W1536656161","https://openalex.org/W1966032405","https://openalex.org/W1974742506","https://openalex.org/W1978006373","https://openalex.org/W1983829281","https://openalex.org/W2011270065","https://openalex.org/W2011879093","https://openalex.org/W2014333016","https://openalex.org/W2070604634","https://openalex.org/W2082667595","https://openalex.org/W2091976335","https://openalex.org/W2098670919","https://openalex.org/W2106431196","https://openalex.org/W2121187169","https://openalex.org/W2127987118","https://openalex.org/W2145258144","https://openalex.org/W2160273239","https://openalex.org/W2161578447","https://openalex.org/W2164631843","https://openalex.org/W2167115386","https://openalex.org/W2170021087","https://openalex.org/W2321585011","https://openalex.org/W2501490139","https://openalex.org/W2506941132","https://openalex.org/W2742706031","https://openalex.org/W2891154994","https://openalex.org/W2962829267","https://openalex.org/W2964300626","https://openalex.org/W4299589498","https://openalex.org/W6842637831"],"related_works":["https://openalex.org/W2359063982","https://openalex.org/W2360658320","https://openalex.org/W1977614046","https://openalex.org/W2351377961","https://openalex.org/W1942228078","https://openalex.org/W4385270631","https://openalex.org/W2046073294","https://openalex.org/W2086942802","https://openalex.org/W2170408898","https://openalex.org/W4389741222"],"abstract_inverted_index":{"Parameter":[0],"estimation":[1],"of":[2,31,79,97,120,126,132,163],"chirp":[3],"signal":[4,18],"model":[5],"with":[6],"time-varying":[7],"amplitude":[8],"and":[9,35,49,64,68,81,99,104,123,138,144],"additive":[10],"noise":[11],"is":[12,24,72,136,150],"a":[13,53],"critical":[14],"problem":[15],"in":[16],"statistical":[17],"processing.":[19],"A":[20],"statistically":[21],"efficient":[22],"algorithm":[23,108],"proposed":[25,165],"to":[26,66,101,140,159],"estimate":[27],"the":[28,45,76,94,107,133,145,161,164],"nonlinear":[29],"parameters":[30],"frequency":[32,37],"rate":[33],"(FR)":[34],"initial":[36,121],"(IF).":[38],"Initial":[39],"estimates":[40],"are":[41,113],"first":[42],"deduced":[43],"from":[44,62],"ambiguity":[46],"function":[47],"(AF)":[48],"then":[50],"refined":[51,134],"through":[52],"statistics-based":[54],"iterative":[55,111,127],"procedure":[56],"that":[57,75],"improves":[58],"their":[59],"convergence":[60,77,95],"rates":[61,78,96],"Op(N\u22121)":[63],"Op(N\u22122)":[65],"Op(N\u22123/2)":[67],"Op(N\u22125/2),":[69],"respectively.":[70],"It":[71],"worth":[73],"noting":[74],"FR":[80,98],"IF":[82,100],"double":[83],"while":[84],"being":[85],"controlled":[86],"by":[87],"each":[88,91],"other":[89],"at":[90],"iteration,":[92],"causing":[93],"jump":[102],"up":[103],"down":[105],"before":[106],"converges.":[109],"Four":[110],"processes":[112],"considered":[114],"involving":[115],"crossovers":[116],"between":[117],"two":[118,124],"types":[119,125],"estimators":[122,135],"coefficients.":[128],"The":[129],"asymptotic":[130],"distribution":[131],"obtained":[137],"demonstrated":[139],"be":[141],"bivariate":[142],"normal,":[143],"Cram\u00e9r\u2013Rao":[146],"lower":[147],"bound":[148],"(CRLB)":[149],"derived":[151],"for":[152],"each.":[153],"Monte":[154],"Carlo":[155],"simulations":[156],"were":[157],"performed":[158],"verify":[160],"effectiveness":[162],"algorithm.":[166]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
