{"id":"https://openalex.org/W2027118218","doi":"https://doi.org/10.1109/ssp.2014.6884610","title":"On fitting exponentially damped sinusoids","display_name":"On fitting exponentially damped sinusoids","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2027118218","doi":"https://doi.org/10.1109/ssp.2014.6884610","mag":"2027118218"},"language":"en","primary_location":{"id":"doi:10.1109/ssp.2014.6884610","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp.2014.6884610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Workshop on Statistical Signal Processing (SSP)","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/A5070352595","display_name":"Barry G. Quinn","orcid":"https://orcid.org/0000-0003-2215-8098"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Barry G. Quinn","raw_affiliation_strings":["Dept of Statistics, Macquarie University, Sydney, NSW, Australia","Dept. of Stat., Macquarie Univ., Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Dept of Statistics, Macquarie University, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]},{"raw_affiliation_string":"Dept. of Stat., Macquarie Univ., Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5070352595"],"corresponding_institution_ids":["https://openalex.org/I99043593"],"apc_list":null,"apc_paid":null,"fwci":0.2129,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58476832,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"201","last_page":"204"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12300","display_name":"Advanced Electrical Measurement Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12300","display_name":"Advanced Electrical Measurement Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/noise","display_name":"Noise (video)","score":0.5960423946380615},{"id":"https://openalex.org/keywords/exponential-growth","display_name":"Exponential growth","score":0.5870324969291687},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.5674617290496826},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5575975775718689},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.5339310169219971},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5194836854934692},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4825431704521179},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44492673873901367},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.43037715554237366},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.420763224363327},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.407736599445343},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3286047577857971},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20568951964378357},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15346986055374146},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.1298016905784607},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07858887314796448}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5960423946380615},{"id":"https://openalex.org/C75235859","wikidata":"https://www.wikidata.org/wiki/Q582659","display_name":"Exponential growth","level":2,"score":0.5870324969291687},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.5674617290496826},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5575975775718689},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.5339310169219971},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5194836854934692},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4825431704521179},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44492673873901367},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.43037715554237366},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.420763224363327},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.407736599445343},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3286047577857971},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20568951964378357},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15346986055374146},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.1298016905784607},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07858887314796448},{"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/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssp.2014.6884610","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp.2014.6884610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Workshop on Statistical Signal Processing (SSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W84548831","https://openalex.org/W2006653047","https://openalex.org/W2071064516","https://openalex.org/W2080655656","https://openalex.org/W2103820741","https://openalex.org/W2107115183","https://openalex.org/W2111855076","https://openalex.org/W2126626320","https://openalex.org/W2139150818","https://openalex.org/W2146884793","https://openalex.org/W2149778355","https://openalex.org/W2159540673","https://openalex.org/W2160044474","https://openalex.org/W2167218293","https://openalex.org/W2170211487","https://openalex.org/W2319003341","https://openalex.org/W2807851516","https://openalex.org/W3142110613","https://openalex.org/W6608423124","https://openalex.org/W6752266270"],"related_works":["https://openalex.org/W2788344745","https://openalex.org/W2062336688","https://openalex.org/W2910677864","https://openalex.org/W2046078371","https://openalex.org/W2383820648","https://openalex.org/W4245445763","https://openalex.org/W3162209258","https://openalex.org/W2054128830","https://openalex.org/W4319736142","https://openalex.org/W2148213881"],"abstract_inverted_index":{"There":[0],"is":[1,87,98],"an":[2],"enormous":[3],"literature":[4],"associated":[5],"with":[6,34,45],"the":[7,10,26,29,38,57,61,64,74,93,103],"estimation":[8,27],"of":[9,12,28,31,56,66,105],"parameters":[11,30],"a":[13,46,83],"sinusoid":[14],"in":[15,52],"additive":[16],"noise.":[17],"While":[18],"there":[19],"has":[20],"been":[21],"less":[22],"work":[23,104],"devoted":[24],"to":[25,60],"noisy":[32],"sinusoids":[33],"exponentially":[35],"damped":[36],"amplitudes,":[37],"two":[39],"problems":[40],"have":[41],"equally":[42],"long":[43],"histories,":[44],"common":[47],"solution":[48],"proposed":[49],"by":[50],"Prony":[51],"1795":[53],"[1].":[54],"Most":[55],"modern":[58],"approaches":[59],"problem":[62],"involve":[63],"use":[65],"sample":[67],"autocovariances.":[68],"In":[69],"this":[70],"paper,":[71],"we":[72],"review":[73],"nonlinear":[75],"regression":[76],"based":[77],"approaches,":[78],"and":[79,81],"describe":[80],"analyse":[82],"`frequency-domain'":[84],"approach":[85],"that":[86],"inherently":[88],"much":[89],"more":[90],"accurate":[91],"than":[92],"covariance-based":[94],"approach,":[95],"but":[96],"which":[97],"also":[99],"computationally":[100],"efficient,":[101],"extending":[102],"Aboutanios":[106],"[2].":[107]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
