{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T18:52:23Z","timestamp":1726253543694},"reference-count":31,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2015,4,1]],"date-time":"2015-04-01T00:00:00Z","timestamp":1427846400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61340044"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","award":["YWF-10-01-B30"],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Signal Processing"],"published-print":{"date-parts":[[2015,4]]},"DOI":"10.1016\/j.sigpro.2014.10.038","type":"journal-article","created":{"date-parts":[[2014,11,16]],"date-time":"2014-11-16T18:22:31Z","timestamp":1416162151000},"page":"95-109","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":125,"special_numbering":"C","title":["EMD interval thresholding denoising based on similarity measure to select relevant modes"],"prefix":"10.1016","volume":"109","author":[{"given":"Gongliu","family":"Yang","sequence":"first","affiliation":[]},{"given":"Yuanyuan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Yanyong","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Zhanlong","family":"Zhu","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.sigpro.2014.10.038_bib1","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1098\/rspa.1998.0193","article-title":"The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis","volume":"454","author":"Huang","year":"1998","journal-title":"Proc. R. Soc. Lond. Ser. A"},{"key":"10.1016\/j.sigpro.2014.10.038_bib2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v006.i06","article-title":"Wavelet estimators in nonparametric regression: a comparative simulation study[J]","volume":"6","author":"Antoniadis","year":"2001","journal-title":"J. Stat. Softw."},{"key":"10.1016\/j.sigpro.2014.10.038_bib3","first-page":"127","article-title":"Incorporating information on neighbouring coefficients into wavelet estimation[J]","volume":"63","author":"Cai","year":"2001","journal-title":"Sankhya: Indian J. Stat."},{"key":"10.1016\/j.sigpro.2014.10.038_bib4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.sigpro.2013.04.015","article-title":"Wavelets for fault diagnosis of rotary machines: a review with applications[J]","volume":"96","author":"Yan","year":"2014","journal-title":"Signal Process."},{"key":"10.1016\/j.sigpro.2014.10.038_bib5","doi-asserted-by":"crossref","first-page":"801","DOI":"10.1016\/j.neucom.2004.10.077","article-title":"Empirical mode decomposition: a method for analyzing neural data[J]","volume":"65","author":"Liang","year":"2005","journal-title":"Neurocomputing"},{"issue":"4","key":"10.1016\/j.sigpro.2014.10.038_bib6","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1016\/j.sigpro.2005.06.011","article-title":"Speech pitch determination based on Hilbert-Huang transform[J]","volume":"86","author":"Huang","year":"2006","journal-title":"Signal Process."},{"issue":"9","key":"10.1016\/j.sigpro.2014.10.038_bib7","doi-asserted-by":"crossref","first-page":"1961","DOI":"10.1016\/j.sigpro.2011.09.014","article-title":"A formal study of the nonlinearity and consistency of the empirical mode decomposition[J]","volume":"92","author":"Tsakalozos","year":"2012","journal-title":"Signal Process."},{"issue":"6","key":"10.1016\/j.sigpro.2014.10.038_bib8","doi-asserted-by":"crossref","first-page":"1597","DOI":"10.1098\/rspa.2003.1221","article-title":"A study of the characteristics of white noise using the empirical mode decomposition method","volume":"460","author":"Wu","year":"2004","journal-title":"Proc. R. Soc. Lond., Ser. A: Math., Phys. Eng. Sci."},{"issue":"2","key":"10.1016\/j.sigpro.2014.10.038_bib9","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1109\/LSP.2003.821662","article-title":"Empirical mode decomposition as filter bank[J]","volume":"11","author":"Flandrin","year":"2004","journal-title":"IEEE Signal Process. Lett."},{"key":"10.1016\/j.sigpro.2014.10.038_bib10","unstructured":"G. Rilling, P. Flandrin, P. Goncalves, Empirical model decomposition, fractional Gaussian noise and hurst exponent estimation, in: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 4, 2005, pp. 489\u2013492."},{"issue":"4","key":"10.1016\/j.sigpro.2014.10.038_bib11","first-page":"312","article-title":"An EMD based simulation of fractional Gaussian noise","volume":"1","author":"Shan","year":"2007","journal-title":"Int. J. Math. Comput. Simul."},{"key":"10.1016\/j.sigpro.2014.10.038_bib12","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1016\/j.sigpro.2013.10.002","article-title":"Simplified noise model parameter estimation for signal-dependent noise[J]","volume":"96","author":"Jeong","year":"2014","journal-title":"Signal Process."},{"issue":"1","key":"10.1016\/j.sigpro.2014.10.038_bib13","first-page":"33","article-title":"EMD-based signal noise reduction[J]","volume":"1","author":"Boudraa","year":"2004","journal-title":"Int. J. Signal Process."},{"key":"10.1016\/j.sigpro.2014.10.038_bib14","unstructured":"A.O. Boudraa, J.C. Cexus, Denoising via empirical mode decomposition[J], in: Proceedings of IEEE International Symposium on Control Communications and Signal Processing(ISCCSP), vol. 4, 2006, pp. 4\u20138."},{"issue":"6","key":"10.1016\/j.sigpro.2014.10.038_bib15","doi-asserted-by":"crossref","first-page":"2196","DOI":"10.1109\/TIM.2007.907967","article-title":"EMD-based signal filtering","volume":"56","author":"Boudraa","year":"2007","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"1","key":"10.1016\/j.sigpro.2014.10.038_bib16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1142\/S1793536910000367","article-title":"A criterion for selecting relevant intrinsic mode functions in empirical mode decomposition[J]","volume":"2","author":"Ayenu-Prah","year":"2010","journal-title":"Adv. Adapt. Data Anal."},{"issue":"8","key":"10.1016\/j.sigpro.2014.10.038_bib17","doi-asserted-by":"crossref","first-page":"085","DOI":"10.1088\/0957-0233\/21\/8\/085106","article-title":"A correlated empirical mode decomposition method for partial discharge signal denoising","volume":"21","author":"Tang","year":"2010","journal-title":"Meas. Sci. Technol."},{"key":"10.1016\/j.sigpro.2014.10.038_bib18","unstructured":"Y. Kopsinis, S. McLaughlin, Empirical mode decomposition based denoising techniques, 1st IAPR International Workshop on Cognitive Information Processing(CIP), Santorini, Greece, 2008, pp. 42\u201347."},{"key":"10.1016\/j.sigpro.2014.10.038_bib19","unstructured":"Y. Kopsinis, S. Mclanglin, Empirical mode decomposition based soft thresholding, in: Proceedings of the 16th European Signal Processing Conference, (EUSIPCO), Lausanne, Switzerland, 2008."},{"issue":"4","key":"10.1016\/j.sigpro.2014.10.038_bib20","doi-asserted-by":"crossref","first-page":"1351","DOI":"10.1109\/TSP.2009.2013885","article-title":"Development of EMD-based denoising methods inspired by wavelet thresholding[J]","volume":"57","author":"Kopsinis","year":"2009","journal-title":"IEEE Trans. Signal Process."},{"issue":"1","key":"10.1016\/j.sigpro.2014.10.038_bib21","doi-asserted-by":"crossref","first-page":"67","DOI":"10.3724\/SP.J.1004.2010.00067","article-title":"A modified empirical mode decomposition method in applications to signal de-noising[J]","volume":"36","author":"Qu","year":"2010","journal-title":"Acta Autom. Sin."},{"key":"10.1016\/j.sigpro.2014.10.038_bib22","doi-asserted-by":"crossref","unstructured":"A. Komaty, A.O. Boudraa, D. Dare, EMD-based filtering using the Hausdoff distance, in: Proceedings of IEEE International Symposium on Signal Processing and Information Technology(ISSPIT), vol. 2, 2012, pp. 292\u2013297.","DOI":"10.1109\/ISSPIT.2012.6621303"},{"issue":"1","key":"10.1016\/j.sigpro.2014.10.038_bib23","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1109\/TIM.2013.2275243","article-title":"EMD-based filtering using similarity measure between probability density functions of IMFs[J]","volume":"63","author":"Komaty","year":"2014","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.sigpro.2014.10.038_bib24","first-page":"74","article-title":"Empirical mode decomposition revisited by multicomponent non smooth convex optimization[J]","author":"Pustelnik","year":"2014","journal-title":"Signal Process."},{"key":"10.1016\/j.sigpro.2014.10.038_bib25","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1093\/biomet\/81.3.425","article-title":"Ideal spatial adaptation by wavelet shrinkage[J]","volume":"81","author":"Donoho","year":"1994","journal-title":"Biometrika"},{"key":"10.1016\/j.sigpro.2014.10.038_bib26","series-title":"\u201cEMD Equivalent Filter Banks, From Interpretation to Applications\u201d in Hilbert-Huang Transform and Its Applications","author":"Flandrin","year":"2005"},{"key":"10.1016\/j.sigpro.2014.10.038_bib27","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.physa.2014.01.020","article-title":"On the computational complexity of the empirical mode decomposition algorithm[J]","volume":"400","author":"Wang","year":"2014","journal-title":"Phys. A"},{"key":"10.1016\/j.sigpro.2014.10.038_bib28","unstructured":"G. Rilling, Empirical mode decomposition [Online]. Available from: \u3008http:\/\/perso.ens-lyon.fr\/patrick.flandrin\/emd.html\u3009, May 10, 2008."},{"issue":"6","key":"10.1016\/j.sigpro.2014.10.038_bib29","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1016\/j.measurement.2009.01.017","article-title":"A novel hybrid EMD-based drift denoising method for a dynamically tuned gyroscope(DTG)[J]","volume":"42","author":"Li","year":"2009","journal-title":"Measurement"},{"key":"10.1016\/j.sigpro.2014.10.038_bib30","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.measurement.2013.11.030","article-title":"An EMD threshold de-noising method for inertial sensors[J]","volume":"49","author":"Gan","year":"2014","journal-title":"Measurement"},{"key":"10.1016\/j.sigpro.2014.10.038_bib31","doi-asserted-by":"crossref","first-page":"1192","DOI":"10.1016\/j.ijleo.2013.07.161","article-title":"An innovation based random weighting estimation mechanism for denoising fiber optic gyro drift signal[J]","volume":"125","author":"Narasimhappa","year":"2014","journal-title":"Optik"}],"container-title":["Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0165168414005027?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0165168414005027?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2020,5,12]],"date-time":"2020-05-12T08:52:10Z","timestamp":1589273530000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0165168414005027"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,4]]},"references-count":31,"alternative-id":["S0165168414005027"],"URL":"https:\/\/doi.org\/10.1016\/j.sigpro.2014.10.038","relation":{},"ISSN":["0165-1684"],"issn-type":[{"value":"0165-1684","type":"print"}],"subject":[],"published":{"date-parts":[[2015,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"EMD interval thresholding denoising based on similarity measure to select relevant modes","name":"articletitle","label":"Article Title"},{"value":"Signal Processing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.sigpro.2014.10.038","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"Copyright \u00a9 2014 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}]}}