{"id":"https://openalex.org/W1985274025","doi":"https://doi.org/10.1142/s1793536910000604","title":"ON THE FILTERING PROPERTIES OF THE EMPIRICAL MODE DECOMPOSITION","display_name":"ON THE FILTERING PROPERTIES OF THE EMPIRICAL MODE DECOMPOSITION","publication_year":2010,"publication_date":"2010-10-01","ids":{"openalex":"https://openalex.org/W1985274025","doi":"https://doi.org/10.1142/s1793536910000604","mag":"1985274025"},"language":"en","primary_location":{"id":"doi:10.1142/s1793536910000604","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793536910000604","pdf_url":null,"source":{"id":"https://openalex.org/S16439242","display_name":"Advances in Adaptive Data Analysis","issn_l":"1793-5369","issn":["1793-5369","1793-7175"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Adaptive Data Analysis","raw_type":"journal-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/A5087187626","display_name":"Zhaohua Wu","orcid":"https://orcid.org/0000-0003-1660-0724"},"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":true,"raw_author_name":"ZHAOHUA WU","raw_affiliation_strings":["Department of Earth, Ocean and Atmospheric Science &amp; Center for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, FL 32306, USA"],"affiliations":[{"raw_affiliation_string":"Department of Earth, Ocean and Atmospheric Science &amp; Center for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, FL 32306, USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110969892","display_name":"Norden E. Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"NORDEN E. HUANG","raw_affiliation_strings":["Research Center for Adaptive Data Analysis, National Central University, Chungli, Taiwan 32001, ROC"],"affiliations":[{"raw_affiliation_string":"Research Center for Adaptive Data Analysis, National Central University, Chungli, Taiwan 32001, ROC","institution_ids":["https://openalex.org/I22265921"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087187626"],"corresponding_institution_ids":["https://openalex.org/I103163165"],"apc_list":null,"apc_paid":null,"fwci":11.6652,"has_fulltext":false,"cited_by_count":106,"citation_normalized_percentile":{"value":0.98237366,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"02","issue":"04","first_page":"397","last_page":"414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9993000030517578,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9923999905586243,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9847999811172485,"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/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.8287041783332825},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7358624935150146},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5946916937828064},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.594182014465332},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4903888702392578},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.48073625564575195},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44199004769325256},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.43933433294296265},{"id":"https://openalex.org/keywords/window-function","display_name":"Window function","score":0.43878495693206787},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.41809701919555664},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3707665503025055},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.2866497039794922},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23497650027275085},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.22836381196975708},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20357003808021545},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.15612462162971497}],"concepts":[{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.8287041783332825},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7358624935150146},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5946916937828064},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.594182014465332},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4903888702392578},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.48073625564575195},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44199004769325256},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.43933433294296265},{"id":"https://openalex.org/C140101238","wikidata":"https://www.wikidata.org/wiki/Q1404885","display_name":"Window function","level":3,"score":0.43878495693206787},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.41809701919555664},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3707665503025055},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.2866497039794922},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23497650027275085},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.22836381196975708},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20357003808021545},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.15612462162971497},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s1793536910000604","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793536910000604","pdf_url":null,"source":{"id":"https://openalex.org/S16439242","display_name":"Advances in Adaptive Data Analysis","issn_l":"1793-5369","issn":["1793-5369","1793-7175"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Adaptive Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6700000166893005}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309292","display_name":"Princeton University","ror":"https://ror.org/00hx57361"},{"id":"https://openalex.org/F4320309398","display_name":"California Institute of Technology","ror":"https://ror.org/05dxps055"},{"id":"https://openalex.org/F4320321040","display_name":"National Science Council","ror":"https://ror.org/02kv4zf79"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W181246441","https://openalex.org/W2007221293","https://openalex.org/W2015544881","https://openalex.org/W2028497691","https://openalex.org/W2085492612","https://openalex.org/W2098395403","https://openalex.org/W2106665847","https://openalex.org/W2107558893","https://openalex.org/W2114193021","https://openalex.org/W2120390927","https://openalex.org/W2122470043","https://openalex.org/W2160097539","https://openalex.org/W2160724632","https://openalex.org/W2165761444","https://openalex.org/W2477788535","https://openalex.org/W4232380507","https://openalex.org/W4296928088"],"related_works":["https://openalex.org/W2081563414","https://openalex.org/W2363056446","https://openalex.org/W2359718298","https://openalex.org/W2377062149","https://openalex.org/W3014107421","https://openalex.org/W2076661204","https://openalex.org/W2380939102","https://openalex.org/W2011248322","https://openalex.org/W2127575060","https://openalex.org/W2066510366"],"abstract_inverted_index":{"The":[0,17],"empirical":[1],"mode":[2],"decomposition":[3,218],"(EMD)":[4],"based":[5],"time-frequency":[6],"analysis":[7],"has":[8],"been":[9],"used":[10,69],"in":[11,22],"many":[12],"scientific":[13],"and":[14,110,119,219],"engineering":[15],"fields.":[16],"mathematical":[18],"expression":[19],"of":[20,31,49,90,101,106,168,211,214],"EMD":[21,57,105,132,174,215],"the":[23,32,39,42,50,53,56,87,102,117,131,149,157,166,196,200,212],"time-frequency-energy":[24],"domain":[25],"appears":[26],"to":[27,38,61,70,78,129,134,147,183,190,208,216],"be":[28,45,181],"a":[29,46,64,107,126,138,169,184,187],"generalization":[30],"Fourier":[33],"transform":[34],"(FT),":[35],"which":[36],"leads":[37],"speculation":[40],"that":[41,141,165,191],"latter":[43],"may":[44],"special":[47],"case":[48],"former.":[51],"On":[52],"other":[54],"hand,":[55],"is":[58,123,162],"also":[59,163],"known":[60],"behave":[62],"like":[63],"dyadic":[65],"filter":[66,135,150],"bank":[67],"when":[68],"decompose":[71],"white":[72,111],"noise.":[73],"These":[74,204],"two":[75],"observations":[76],"seem":[77],"contradict":[79],"each":[80],"other.":[81],"In":[82],"this":[83],"paper,":[84],"we":[85,113],"study":[86],"filtering":[88,139],"properties":[89],"EMD,":[91],"as":[92,116,156,199],"its":[93],"sifting":[94,121,158,178,201],"number":[95,122,128,159,179,202],"changes.":[96,203],"Based":[97],"on":[98],"numerical":[99],"results":[100,205],"decompositions":[103],"using":[104],"delta":[108,170],"function":[109,171],"noise,":[112],"conjecture":[114],"that,":[115],"(pre-assigned":[118],"fixed)":[120],"changed":[124],"from":[125,144,173,192],"small":[127],"infinity,":[130],"corresponds":[133],"banks":[136],"with":[137,175],"ratio":[140],"changes":[142],"accordingly":[143],"2":[145],"(dyadic)":[146],"1;":[148],"window":[151],"does":[152],"not":[153],"narrow":[154],"accordingly,":[155],"increases.":[160],"It":[161],"demonstrated":[164],"components":[167],"resulted":[172],"any":[176],"prescribed":[177],"can":[180],"rescaled":[182],"single":[185],"shape,":[186],"result":[188],"similar":[189],"wavelet":[193,217],"decomposition,":[194],"although":[195],"shape":[197],"changes,":[198],"will":[206],"lead":[207],"further":[209],"understandings":[210],"relations":[213],"FT.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":9},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":5}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
