{"id":"https://openalex.org/W2085206773","doi":"https://doi.org/10.1109/icassp.1986.1168699","title":"Spectral line tracking for nonstationary random processes","display_name":"Spectral line tracking for nonstationary random processes","publication_year":2005,"publication_date":"2005-03-24","ids":{"openalex":"https://openalex.org/W2085206773","doi":"https://doi.org/10.1109/icassp.1986.1168699","mag":"2085206773"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1986.1168699","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1986.1168699","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '86. 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/A5017841865","display_name":"D.M. Wilkes","orcid":"https://orcid.org/0000-0002-9693-3539"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D. Wilkes","raw_affiliation_strings":["School of Electrical Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003883627","display_name":"M.H. Hayes","orcid":"https://orcid.org/0000-0002-5252-1241"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M. Hayes","raw_affiliation_strings":["School of Electrical Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"2347","last_page":"2350"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11236","display_name":"Control Systems and Identification","score":0.9940000176429749,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9927999973297119,"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/white-noise","display_name":"White noise","score":0.6422008872032166},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.5893875360488892},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.578679084777832},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5350573658943176},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.5343669056892395},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5239531993865967},{"id":"https://openalex.org/keywords/autocorrelation-matrix","display_name":"Autocorrelation matrix","score":0.5191646814346313},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5015277862548828},{"id":"https://openalex.org/keywords/eigendecomposition-of-a-matrix","display_name":"Eigendecomposition of a matrix","score":0.4896884262561798},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.45962560176849365},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4492364227771759},{"id":"https://openalex.org/keywords/power-iteration","display_name":"Power iteration","score":0.43797069787979126},{"id":"https://openalex.org/keywords/noise-power","display_name":"Noise power","score":0.4361233711242676},{"id":"https://openalex.org/keywords/harmonic","display_name":"Harmonic","score":0.4183726906776428},{"id":"https://openalex.org/keywords/stochastic-process","display_name":"Stochastic process","score":0.41631200909614563},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3903800845146179},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.34153062105178833},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.13465696573257446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11968952417373657},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10247480869293213},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07114425301551819}],"concepts":[{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.6422008872032166},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.5893875360488892},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.578679084777832},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5350573658943176},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.5343669056892395},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5239531993865967},{"id":"https://openalex.org/C4033963","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation matrix","level":3,"score":0.5191646814346313},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5015277862548828},{"id":"https://openalex.org/C169756996","wikidata":"https://www.wikidata.org/wiki/Q194919","display_name":"Eigendecomposition of a matrix","level":3,"score":0.4896884262561798},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.45962560176849365},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4492364227771759},{"id":"https://openalex.org/C162443888","wikidata":"https://www.wikidata.org/wiki/Q1426504","display_name":"Power iteration","level":3,"score":0.43797069787979126},{"id":"https://openalex.org/C203234222","wikidata":"https://www.wikidata.org/wiki/Q2133519","display_name":"Noise power","level":3,"score":0.4361233711242676},{"id":"https://openalex.org/C127934551","wikidata":"https://www.wikidata.org/wiki/Q1148098","display_name":"Harmonic","level":2,"score":0.4183726906776428},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.41631200909614563},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3903800845146179},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.34153062105178833},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.13465696573257446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11968952417373657},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10247480869293213},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07114425301551819},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1986.1168699","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1986.1168699","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '86. 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":10,"referenced_works":["https://openalex.org/W1524302018","https://openalex.org/W1872966320","https://openalex.org/W1988889311","https://openalex.org/W2010659045","https://openalex.org/W2019833178","https://openalex.org/W2020729167","https://openalex.org/W2030740216","https://openalex.org/W2059586807","https://openalex.org/W2568342123","https://openalex.org/W6631236898"],"related_works":["https://openalex.org/W2380081160","https://openalex.org/W2087650113","https://openalex.org/W2051830505","https://openalex.org/W2383442806","https://openalex.org/W3016895370","https://openalex.org/W2549750102","https://openalex.org/W1875741523","https://openalex.org/W2030740216","https://openalex.org/W2114157553","https://openalex.org/W4313156156"],"abstract_inverted_index":{"The":[0],"harmonic":[1],"decomposition":[2],"of":[3,10,24,30,33,59,69,76,90,97,124,152],"a":[4,8,22,28,116],"random":[5],"process":[6],"into":[7],"sum":[9],"sinusoids":[11,99],"in":[12,21,170],"white":[13,46],"noise":[14,47],"is":[15],"an":[16],"important":[17],"problem":[18],"with":[19],"applications":[20],"number":[23],"different":[25],"areas.":[26],"As":[27],"result":[29],"the":[31,41,45,52,56,60,70,74,91,95,98,111,125,134,145,153,159],"work":[32],"V.F.":[34],"Pisarenko,":[35],"it":[36],"has":[37],"been":[38],"shown":[39],"that":[40,144],"sinusoidal":[42],"frequencies":[43,96,154],"and":[44,55,114],"power":[48],"are":[49,103,130],"determined":[50],"by":[51],"minimum":[53],"eigenvalue":[54],"corresponding":[57],"eigenvector":[58],"autocorrelation":[61],"matrix.":[62],"Many":[63],"authors":[64],"have":[65,82],"formulated":[66],"adaptive":[67,160],"versions":[68],"Pisarenko":[71],"solution":[72],"for":[73,121],"purpose":[75],"spectral":[77],"line":[78],"tracking,":[79],"but":[80],"most":[81,89],"concentrated":[83],"only":[84],"on":[85,110],"stationary":[86],"sinusoids.":[87,173],"In":[88,105],"interesting":[92],"applications,":[93],"however,":[94],"change,":[100],"thus":[101],"they":[102],"nonstationary.":[104],"this":[106],"paper":[107],"we":[108],"concentrate":[109],"nonstationary":[112,172],"case,":[113],"propose":[115],"novel":[117],"fast":[118],"iterative":[119,135],"technique":[120],"real-time":[122],"tracking":[123,171],"time-varying":[126],"frequencies.":[127],"Simulation":[128],"examples":[129,142],"given":[131],"which":[132],"compare":[133],"method":[136,147],"to":[137,149,167],"other":[138],"data-adaptive":[139],"techniques.":[140],"These":[141],"show":[143],"proposed":[146],"converges":[148],"good":[150],"estimates":[151],"much":[155],"more":[156],"quickly":[157],"than":[158],"techniques":[161],"as":[162,164],"well":[163],"being":[165],"able":[166],"perform":[168],"better":[169]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}