{"id":"https://openalex.org/W2109896502","doi":"https://doi.org/10.1109/tsp.2009.2013885","title":"Development of EMD-Based Denoising Methods Inspired by Wavelet Thresholding","display_name":"Development of EMD-Based Denoising Methods Inspired by Wavelet Thresholding","publication_year":2009,"publication_date":"2009-01-28","ids":{"openalex":"https://openalex.org/W2109896502","doi":"https://doi.org/10.1109/tsp.2009.2013885","mag":"2109896502"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2009.2013885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2009.2013885","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","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/A5011578490","display_name":"Yannis Kopsinis","orcid":null},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Y. Kopsinis","raw_affiliation_strings":["Institute of Digital Communications, School of Engineering and Electronics, University of Edinburgh, Edinburgh, UK","Sch. of Eng. & Electron., Univ. of Edinburgh, Edinburgh"],"affiliations":[{"raw_affiliation_string":"Institute of Digital Communications, School of Engineering and Electronics, University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"Sch. of Eng. & Electron., Univ. of Edinburgh, Edinburgh","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010538525","display_name":"Stephen McLaughlin","orcid":"https://orcid.org/0000-0002-9558-8294"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"S. McLaughlin","raw_affiliation_strings":["Institute of Digital Communications, School of Engineering and Electronics, University of Edinburgh, Edinburgh, UK","Sch. of Eng. & Electron., Univ. of Edinburgh, Edinburgh"],"affiliations":[{"raw_affiliation_string":"Institute of Digital Communications, School of Engineering and Electronics, University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"Sch. of Eng. & Electron., Univ. of Edinburgh, Edinburgh","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5011578490"],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":40.0319,"has_fulltext":false,"cited_by_count":671,"citation_normalized_percentile":{"value":0.99841907,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"57","issue":"4","first_page":"1351","last_page":"1362"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9990000128746033,"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":0.9990000128746033,"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":0.9950000047683716,"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":0.9916999936103821,"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/thresholding","display_name":"Thresholding","score":0.825446367263794},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.7559200525283813},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.7048871517181396},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.70219886302948},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.645136296749115},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6337828636169434},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5067926049232483},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.479114294052124},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.4630546569824219},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44796517491340637},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3631068468093872},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.21247419714927673},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11837363243103027},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.06236600875854492}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.825446367263794},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.7559200525283813},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.7048871517181396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.70219886302948},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.645136296749115},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6337828636169434},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5067926049232483},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.479114294052124},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.4630546569824219},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44796517491340637},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3631068468093872},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.21247419714927673},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11837363243103027},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.06236600875854492}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2009.2013885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2009.2013885","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W18046889","https://openalex.org/W198953946","https://openalex.org/W1522743418","https://openalex.org/W1538522523","https://openalex.org/W1905397622","https://openalex.org/W1964642289","https://openalex.org/W1967939429","https://openalex.org/W2005469478","https://openalex.org/W2007221293","https://openalex.org/W2025538567","https://openalex.org/W2064187243","https://openalex.org/W2098395403","https://openalex.org/W2109500956","https://openalex.org/W2115755118","https://openalex.org/W2138402108","https://openalex.org/W2158940042","https://openalex.org/W2160097539","https://openalex.org/W2163171173","https://openalex.org/W2166089572","https://openalex.org/W2188563164","https://openalex.org/W2189367262","https://openalex.org/W2504528620","https://openalex.org/W2737101842","https://openalex.org/W3151807103","https://openalex.org/W4214806317","https://openalex.org/W4230626425","https://openalex.org/W4237207237","https://openalex.org/W6631329752","https://openalex.org/W6632174267","https://openalex.org/W6741692844"],"related_works":["https://openalex.org/W2080197880","https://openalex.org/W2133587243","https://openalex.org/W2054017055","https://openalex.org/W2034318424","https://openalex.org/W2085792030","https://openalex.org/W1588899229","https://openalex.org/W1976022598","https://openalex.org/W4321517526","https://openalex.org/W1918078477","https://openalex.org/W2111896212"],"abstract_inverted_index":{"One":[0],"of":[1,58,78],"the":[2,25,34,41,65,75,79,84,89],"tasks":[3],"for":[4,19,28],"which":[5,20],"empirical":[6],"mode":[7],"decomposition":[8,42,81],"(EMD)":[9],"is":[10,13,38,61,100],"potentially":[11],"useful":[12],"nonparametric":[14],"signal":[15],"denoising,":[16],"an":[17],"area":[18],"wavelet":[21,35,92],"thresholding":[22,36],"has":[23],"been":[24],"dominant":[26],"technique":[27,96],"many":[29],"years.":[30],"In":[31,83],"this":[32,59],"paper,":[33],"principle":[37,60],"used":[39],"in":[40,64],"modes":[43],"resulting":[44],"from":[45],"applying":[46],"EMD":[47,66,80,99],"to":[48,98,103],"a":[49,55,94],"signal.":[50],"We":[51],"show":[52],"that":[53],"although":[54],"direct":[56],"application":[57],"not":[62],"feasible":[63],"case,":[67],"it":[68],"can":[69],"be":[70],"appropriately":[71],"adapted":[72,97],"by":[73,88],"exploiting":[74],"special":[76],"characteristics":[77],"modes.":[82],"same":[85],"manner,":[86],"inspired":[87],"translation":[90],"invariant":[91],"thresholding,":[93],"similar":[95],"developed,":[101],"leading":[102],"enhanced":[104],"denoising":[105],"performance.":[106]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":33},{"year":2024,"cited_by_count":45},{"year":2023,"cited_by_count":49},{"year":2022,"cited_by_count":56},{"year":2021,"cited_by_count":46},{"year":2020,"cited_by_count":61},{"year":2019,"cited_by_count":64},{"year":2018,"cited_by_count":49},{"year":2017,"cited_by_count":50},{"year":2016,"cited_by_count":50},{"year":2015,"cited_by_count":39},{"year":2014,"cited_by_count":36},{"year":2013,"cited_by_count":33},{"year":2012,"cited_by_count":18}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
