{"id":"https://openalex.org/W1576580361","doi":"https://doi.org/10.1109/icassp.1987.1169650","title":"An accuracy analysis of the Kumaresan-Tufts method for estimating complex damped exponentials","display_name":"An accuracy analysis of the Kumaresan-Tufts method for estimating complex damped exponentials","publication_year":2005,"publication_date":"2005-03-24","ids":{"openalex":"https://openalex.org/W1576580361","doi":"https://doi.org/10.1109/icassp.1987.1169650","mag":"1576580361"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1987.1169650","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1987.1169650","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5006597702","display_name":"B. Friedlander","orcid":"https://orcid.org/0000-0001-5133-2433"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"B. Friedlander","raw_affiliation_strings":["Saxpy Computer Corporation, Sunnyvale, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saxpy Computer Corporation, Sunnyvale, CA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027216170","display_name":"B. Porat","orcid":null},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"B. Porat","raw_affiliation_strings":["Department of Electrical Engineering Technion, Israel Institute of Technology-Technion, Haifa, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering Technion, Israel Institute of Technology-Technion, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"665","last_page":"668"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9948999881744385,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9948999881744385,"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"}},{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9812999963760376,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9800999760627747,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.7955493927001953},{"id":"https://openalex.org/keywords/truncation","display_name":"Truncation (statistics)","score":0.7369582056999207},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.717628538608551},{"id":"https://openalex.org/keywords/taylor-series","display_name":"Taylor series","score":0.7075676918029785},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.5566415190696716},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5130073428153992},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5045598745346069},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5035638213157654},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.490389347076416},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4771955907344818},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4679485857486725},{"id":"https://openalex.org/keywords/matrix-exponential","display_name":"Matrix exponential","score":0.42821893095970154},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40090465545654297},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3397931754589081},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2643880248069763},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.23870766162872314},{"id":"https://openalex.org/keywords/differential-equation","display_name":"Differential equation","score":0.1390957534313202},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.09806555509567261}],"concepts":[{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.7955493927001953},{"id":"https://openalex.org/C106195933","wikidata":"https://www.wikidata.org/wiki/Q7847935","display_name":"Truncation (statistics)","level":2,"score":0.7369582056999207},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.717628538608551},{"id":"https://openalex.org/C158946198","wikidata":"https://www.wikidata.org/wiki/Q131187","display_name":"Taylor series","level":2,"score":0.7075676918029785},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.5566415190696716},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5130073428153992},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5045598745346069},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5035638213157654},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.490389347076416},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4771955907344818},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4679485857486725},{"id":"https://openalex.org/C195906000","wikidata":"https://www.wikidata.org/wiki/Q1191722","display_name":"Matrix exponential","level":3,"score":0.42821893095970154},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40090465545654297},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3397931754589081},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2643880248069763},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.23870766162872314},{"id":"https://openalex.org/C78045399","wikidata":"https://www.wikidata.org/wiki/Q11214","display_name":"Differential equation","level":2,"score":0.1390957534313202},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.09806555509567261},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/icassp.1987.1169650","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1987.1169650","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","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":5,"referenced_works":["https://openalex.org/W2144817789","https://openalex.org/W2152434530","https://openalex.org/W2165887549","https://openalex.org/W2171369888","https://openalex.org/W2312564560"],"related_works":["https://openalex.org/W1974935850","https://openalex.org/W2074350688","https://openalex.org/W3095815589","https://openalex.org/W1510841924","https://openalex.org/W4313274502","https://openalex.org/W2919248205","https://openalex.org/W3133970298","https://openalex.org/W2021279739","https://openalex.org/W2167705757","https://openalex.org/W2015216402"],"abstract_inverted_index":{"Recently,":[0],"Kumaresan":[1],"and":[2,34,118],"Tufts":[3],"(KT)":[4],"presented":[5],"a":[6,51,70],"method":[7,22,46],"for":[8,61],"estimating":[9],"the":[10,29,39,42,62,75,89,98,111,115,120,123,128,131],"parameters":[11,91,126],"of":[12,28,41,74,88,97,114,122,130],"damped":[13],"exponential":[14],"waveforms":[15],"in":[16,55,106],"additive":[17],"white":[18],"noise.":[19],"The":[20,44,78],"KT":[21,45,76,116],"uses":[23],"singular":[24],"value":[25],"decomposition":[26],"(SVD)":[27],"data":[30],"matrix,":[31],"with":[32,57],"truncation":[33],"backward":[35],"prediction":[36],"to":[37,49],"improve":[38],"accuracy":[40,72,129],"estimates.":[43,132],"was":[47],"demonstrated":[48],"have":[50],"very":[52],"good":[53,112],"performance,":[54],"comparison":[56],"traditional":[58],"methods":[59],"used":[60],"same":[63],"problem.":[64],"In":[65],"this":[66],"paper":[67],"we":[68],"provide":[69],"quantitative":[71],"analysis":[73,79,99],"method.":[77],"is":[80],"based":[81],"on":[82,127],"first":[83],"order":[84],"Taylor":[85],"series":[86],"approximations":[87],"estimated":[90],"around":[92],"their":[93],"true":[94],"values.":[95],"Results":[96],"were":[100],"illustrated":[101],"by":[102],"some":[103],"numerical":[104],"examples":[105],"[3].":[107],"These":[108],"results":[109],"confirm":[110],"performance":[113],"method,":[117],"show":[119],"effect":[121],"user":[124],"chosen":[125]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
