{"id":"https://openalex.org/W3015640421","doi":"https://doi.org/10.1109/icassp40776.2020.9053507","title":"Robust Parameter Estimation of Contaminated Damped Exponentials","display_name":"Robust Parameter Estimation of Contaminated Damped Exponentials","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015640421","doi":"https://doi.org/10.1109/icassp40776.2020.9053507","mag":"3015640421"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053507","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053507","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5015918596","display_name":"Youye Xie","orcid":"https://orcid.org/0000-0003-3646-0079"},"institutions":[{"id":"https://openalex.org/I167576493","display_name":"Colorado School of Mines","ror":"https://ror.org/04raf6v53","country_code":"US","type":"education","lineage":["https://openalex.org/I167576493"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Youye Xie","raw_affiliation_strings":["Department of Electrical Engineering, Colorado School of Mines, Golden, CO, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Colorado School of Mines, Golden, CO, USA","institution_ids":["https://openalex.org/I167576493"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052544518","display_name":"Dehong Liu","orcid":"https://orcid.org/0000-0003-3355-3018"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dehong Liu","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101648073","display_name":"Hassan Mansour","orcid":"https://orcid.org/0000-0002-1667-9885"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hassan Mansour","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034522188","display_name":"Petros T. Boufounos","orcid":"https://orcid.org/0000-0003-1369-0947"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Petros T. Boufounos","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015918596"],"corresponding_institution_ids":["https://openalex.org/I167576493"],"apc_list":null,"apc_paid":null,"fwci":0.7042,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.63997808,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"5500","last_page":"5504"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/gaussian-noise","display_name":"Gaussian noise","score":0.610027015209198},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.5798532962799072},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5443077683448792},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.5254903435707092},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4935213327407837},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4874610900878906},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4841924011707306},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4655991494655609},{"id":"https://openalex.org/keywords/coordinate-descent","display_name":"Coordinate descent","score":0.46336647868156433},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44575759768486023},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.41990649700164795},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.409808874130249},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3489651083946228},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.16798460483551025},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12436705827713013},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08194038271903992},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.07634669542312622}],"concepts":[{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.610027015209198},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.5798532962799072},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5443077683448792},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.5254903435707092},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4935213327407837},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4874610900878906},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4841924011707306},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4655991494655609},{"id":"https://openalex.org/C157553263","wikidata":"https://www.wikidata.org/wiki/Q5168004","display_name":"Coordinate descent","level":2,"score":0.46336647868156433},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44575759768486023},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.41990649700164795},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.409808874130249},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3489651083946228},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.16798460483551025},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12436705827713013},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08194038271903992},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.07634669542312622},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","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/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/icassp40776.2020.9053507","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053507","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1551877493","https://openalex.org/W2065656021","https://openalex.org/W2113096693","https://openalex.org/W2124765774","https://openalex.org/W2124883740","https://openalex.org/W2127411941","https://openalex.org/W2145448160","https://openalex.org/W2145962650","https://openalex.org/W2156814540","https://openalex.org/W2164278908","https://openalex.org/W2171436543","https://openalex.org/W2199059241","https://openalex.org/W2472411061","https://openalex.org/W2557989537","https://openalex.org/W2767933257","https://openalex.org/W2802232947","https://openalex.org/W2892056924","https://openalex.org/W2902939049","https://openalex.org/W2940390049","https://openalex.org/W2962694024","https://openalex.org/W2963391931","https://openalex.org/W2963733763","https://openalex.org/W2969899794","https://openalex.org/W4292363360","https://openalex.org/W6633201472"],"related_works":["https://openalex.org/W2547595264","https://openalex.org/W2986378528","https://openalex.org/W2361550794","https://openalex.org/W3178345791","https://openalex.org/W2092661960","https://openalex.org/W1550854977","https://openalex.org/W2949211747","https://openalex.org/W3005742472","https://openalex.org/W2588855097","https://openalex.org/W2162441712"],"abstract_inverted_index":{"Parameter":[0],"estimation":[1,111],"of":[2,23,39,53,62,85,102],"damped":[3,24,54,63,103,130],"exponential":[4],"signals":[5],"has":[6],"wide":[7],"applications":[8],"including":[9],"fault":[10,131],"detection":[11],"and":[12,68,88,145,155],"system":[13],"parameter":[14,110],"identification,":[15],"etc.":[16],"However,":[17],"existing":[18],"methods":[19,123],"for":[20,108],"estimating":[21],"parameters":[22,52],"exponentials":[25,55,104],"are":[26],"either":[27],"sensitive":[28],"to":[29,33,50,96,142],"noise":[30,40],"or":[31],"restricted":[32],"dealing":[34],"with":[35],"a":[36,60,76,89,98],"certain":[37],"type":[38],"such":[41],"as":[42],"Gaussian":[43,66],"noise.":[44],"In":[45],"this":[46],"paper":[47],"we":[48],"aim":[49],"estimate":[51],"from":[56,105,133],"contaminated":[57],"signal,":[58],"i.e.,":[59],"mixture":[61],"exponentials,":[64],"random":[65],"noise,":[67],"spike":[69],"interference.":[70],"We":[71],"propose":[72],"two":[73],"robust":[74],"approaches,":[75],"convex":[77,138],"one":[78,91,151],"solved":[79,92],"by":[80,93],"the":[81,113,137,149],"alternating":[82],"direction":[83],"method":[84],"multipliers":[86],"(ADMM)":[87],"non-convex":[90,150],"coordinate":[94],"descent,":[95],"recovering":[97],"low-rank":[99],"Hankel":[100],"matrix":[101,114],"noisy":[106,134],"measurements":[107],"further":[109],"using":[112],"pencil":[115],"technique.":[116],"Numerical":[117],"experiments":[118],"show":[119],"that":[120],"our":[121],"proposed":[122],"outperform":[124],"classical":[125],"ones":[126],"in":[127],"detecting":[128],"small":[129],"signatures":[132],"measurements.":[135],"While":[136],"approach":[139],"is":[140],"amenable":[141],"theoretical":[143],"analysis":[144],"global":[146],"convergence":[147],"guarantees,":[148],"exhibits":[152],"more":[153],"robustness":[154],"computational":[156],"efficiency.":[157]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
