{"id":"https://openalex.org/W2055442689","doi":"https://doi.org/10.1109/isit.2007.4557480","title":"Estimation of the Frequency of Sinusoidal Signals in Laplace Noise","display_name":"Estimation of the Frequency of Sinusoidal Signals in Laplace Noise","publication_year":2007,"publication_date":"2007-06-01","ids":{"openalex":"https://openalex.org/W2055442689","doi":"https://doi.org/10.1109/isit.2007.4557480","mag":"2055442689"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2007.4557480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2007.4557480","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Symposium on Information Theory","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/A5043835745","display_name":"Ta-Hsin Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ta-Hsin Li","raw_affiliation_strings":["Department of Mathematical Sciences, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","IBM, T.J. Watson Research Center, Yorktown Heights"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM, T.J. Watson Research Center, Yorktown Heights","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102938758","display_name":"Kai\u2010Sheng Song","orcid":null},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kai-Sheng Song","raw_affiliation_strings":["Department of Statistics, Florida State University, Tallahassee, FL, USA","Department of Statistics, Florida State University, Tallahassee, FL 32306-4330, USA. kssong@stat.fsu.edu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Florida State University, Tallahassee, FL, USA","institution_ids":["https://openalex.org/I103163165"]},{"raw_affiliation_string":"Department of Statistics, Florida State University, Tallahassee, FL 32306-4330, USA. kssong@stat.fsu.edu","institution_ids":["https://openalex.org/I103163165"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9765,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.75472674,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1786","last_page":"1790"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9991999864578247,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9991999864578247,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9951000213623047,"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/T12300","display_name":"Advanced Electrical Measurement Techniques","score":0.9896000027656555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6404861211776733},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6142021417617798},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.542757511138916},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.5330331325531006},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5189425945281982},{"id":"https://openalex.org/keywords/laplace-transform","display_name":"Laplace transform","score":0.5109142661094666},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4913610517978668},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4878561496734619},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4385106861591339},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4335617423057556},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.42755335569381714},{"id":"https://openalex.org/keywords/cram\u00e9r\u2013rao-bound","display_name":"Cram\u00e9r\u2013Rao bound","score":0.42730945348739624},{"id":"https://openalex.org/keywords/maximum-likelihood-sequence-estimation","display_name":"Maximum likelihood sequence estimation","score":0.4193613827228546},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.41323620080947876},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.4121081829071045},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3937032222747803},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20389387011528015},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.151225745677948},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.12017932534217834}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6404861211776733},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6142021417617798},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.542757511138916},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.5330331325531006},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5189425945281982},{"id":"https://openalex.org/C97937538","wikidata":"https://www.wikidata.org/wiki/Q199691","display_name":"Laplace transform","level":2,"score":0.5109142661094666},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4913610517978668},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4878561496734619},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4385106861591339},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4335617423057556},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.42755335569381714},{"id":"https://openalex.org/C4978587","wikidata":"https://www.wikidata.org/wiki/Q1138810","display_name":"Cram\u00e9r\u2013Rao bound","level":3,"score":0.42730945348739624},{"id":"https://openalex.org/C191462741","wikidata":"https://www.wikidata.org/wiki/Q6795902","display_name":"Maximum likelihood sequence estimation","level":3,"score":0.4193613827228546},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.41323620080947876},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.4121081829071045},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3937032222747803},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20389387011528015},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.151225745677948},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.12017932534217834},{"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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/isit.2007.4557480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2007.4557480","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Symposium on Information Theory","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.329.3046","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.329.3046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.research.ibm.com/people/t/thl/myhtml/freqest/isit07.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1972665666","https://openalex.org/W1984570338","https://openalex.org/W2001188690","https://openalex.org/W2001762009","https://openalex.org/W2010492472","https://openalex.org/W2011270065","https://openalex.org/W2019833178","https://openalex.org/W2043591568","https://openalex.org/W2045936591","https://openalex.org/W2067718036","https://openalex.org/W2089957712","https://openalex.org/W2096990949","https://openalex.org/W2100567194","https://openalex.org/W2103716751","https://openalex.org/W2112815694","https://openalex.org/W2112883107","https://openalex.org/W2122759946","https://openalex.org/W2128131274","https://openalex.org/W2136812492","https://openalex.org/W2138680881","https://openalex.org/W2139547573","https://openalex.org/W2143065331","https://openalex.org/W2149460029","https://openalex.org/W2166764037","https://openalex.org/W2171074980","https://openalex.org/W4213201159"],"related_works":["https://openalex.org/W2103185490","https://openalex.org/W2019724159","https://openalex.org/W2371672232","https://openalex.org/W2103357804","https://openalex.org/W1512911331","https://openalex.org/W2148113631","https://openalex.org/W2110390278","https://openalex.org/W2111646181","https://openalex.org/W2120595071","https://openalex.org/W1967639437"],"abstract_inverted_index":{"Accurate":[0],"estimation":[1],"of":[2,5,35,70,83,109],"the":[3,30,33,48,57,63,71,76,81,85,107,113,118,130],"frequency":[4],"sinusoidal":[6],"signals":[7],"from":[8],"noisy":[9],"observations":[10],"is":[11,53,67],"an":[12],"important":[13],"problem":[14,31],"in":[15,38,43,75,97,112],"signal":[16],"processing":[17],"applications":[18],"such":[19,90],"as":[20,91],"radar,":[21],"sonar,":[22],"and":[23,40,94],"telecommunications.":[24],"In":[25],"this":[26],"paper,":[27],"we":[28],"study":[29],"under":[32,62],"assumption":[34,65],"non-Gaussian":[36,98],"noise":[37,42],"general":[39],"Laplace":[41,49,64],"particular.":[44],"We":[45,100,122],"prove":[46],"that":[47,105],"maximum":[50,119],"likelihood":[51,114,120],"estimator":[52],"able":[54],"to":[55,128],"attain":[56],"asymptotic":[58],"Cramer-Rao":[59,72],"lower":[60,73],"bound":[61,74],"which":[66],"one":[68],"half":[69],"Gaussian":[77],"case.":[78],"This":[79],"provides":[80],"possibility":[82],"improving":[84],"currently":[86],"most":[87],"efficient":[88],"methods":[89],"nonlinear":[92],"least-squares":[93],"periodogram":[95],"maximization":[96],"cases.":[99],"propose":[101],"a":[102],"computational":[103],"procedure":[104],"overcomes":[106],"difficulty":[108],"local":[110],"extrema":[111],"function":[115],"when":[116],"computing":[117],"estimator.":[121],"also":[123],"provide":[124],"some":[125],"simulation":[126],"results":[127],"validate":[129],"proposed":[131],"approach.":[132]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
