{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T15:09:50Z","timestamp":1768748990394,"version":"3.49.0"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2013,1,19]],"date-time":"2013-01-19T00:00:00Z","timestamp":1358553600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Sign Process Syst"],"published-print":{"date-parts":[[2013,10]]},"DOI":"10.1007\/s11265-012-0726-y","type":"journal-article","created":{"date-parts":[[2013,1,18]],"date-time":"2013-01-18T00:01:27Z","timestamp":1358467287000},"page":"43-58","source":"Crossref","is-referenced-by-count":25,"title":["Empirical Mode Decomposition: Real-Time Implementation and Applications"],"prefix":"10.1007","volume":"73","author":[{"given":"Amir","family":"Eftekhar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christofer","family":"Toumazou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emmanuel M.","family":"Drakakis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2013,1,19]]},"reference":[{"key":"726_CR1","unstructured":"Rilling, G., Flandrin, P., Goncalves, P. (2003) On empirical mode decomposition and its algorithms. In IEEE-Eurasip workshop."},{"key":"726_CR2","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1109\/TSP.2007.906771","volume":"56","author":"G Rilling","year":"2008","unstructured":"Rilling, G., & Flandrin, P. (2008). One or two frequencies? The empirical mode decomposition answers. IEEE Transactions on Signal Processing, 56, 85\u201395.","journal-title":"IEEE Transactions on Signal Processing"},{"issue":"1","key":"726_CR3","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1142\/S1793536909000023","volume":"1","author":"G Rilling","year":"2009","unstructured":"Rilling, G., & Flandrin, P. (2009). Sampling effects on the empirical mode decomposition. Advances in Adaptive Data Analysis, 1(1), 43\u201359.","journal-title":"Advances in Adaptive Data Analysis"},{"issue":"1971","key":"726_CR4","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1098\/rspa.1998.0193","volume":"454","author":"NE Huang","year":"1998","unstructured":"Huang, N.E., et al. (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceeding of the Royal Society, 454(1971), 903\u2013995.","journal-title":"Proceeding of the Royal Society"},{"issue":"2","key":"726_CR5","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1093\/brain\/awl241","volume":"130","author":"F Mormann","year":"2007","unstructured":"Mormann, F., Andrzejak, R.G., Elger, C.E., Lehnertz, K. (2007). Seizure prediction: the long and winding road. Brain, 130(2), 314\u2013333.","journal-title":"Brain"},{"issue":"2037","key":"726_CR6","doi-asserted-by":"crossref","first-page":"2317","DOI":"10.1098\/rspa.2003.1123","volume":"459","author":"NE Huang","year":"2003","unstructured":"Huang, N.E., et al. (2003). A confidence limit for the empirical mode decomposition and Hilbert spectral analysis. Proceeding of the Royal Society, 459(2037), 2317\u20132345.","journal-title":"Proceeding of the Royal Society"},{"issue":"6","key":"726_CR7","doi-asserted-by":"crossref","first-page":"1374","DOI":"10.1016\/j.ymssp.2007.11.028","volume":"22","author":"R Rato","year":"2008","unstructured":"Rato, R., Ortigueira, M., Batista, A.G. (2008). On the HHT, its problems, and some solutions. Mechanical Systems and Signal Processing, 22(6), 1374\u20131394.","journal-title":"Mechanical Systems and Signal Processing"},{"key":"726_CR8","doi-asserted-by":"crossref","unstructured":"Eftekhar, A., Vohra, F., Toumazou, C., Drakakis, E.M. (2008) Hilbert\u2013Huang transform: Preliminary studies in epilepsy and cardiac arrhythmias. IEEE BioCAS (373\u2013366).","DOI":"10.1109\/BIOCAS.2008.4696952"},{"issue":"1","key":"726_CR9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1142\/S1793536909000047","volume":"1","author":"Z Wu","year":"2009","unstructured":"Wu, Z., & Hunag, N.E. (2009). Ensemble empirical mode decomposition: a noise assisted data analysis method. Advances in Adaptive Data Analysis, 1(1), 1\u201341.","journal-title":"Advances in Adaptive Data Analysis"},{"issue":"5","key":"726_CR10","doi-asserted-by":"crossref","first-page":"2421","DOI":"10.1109\/TSP.2011.2106779","volume":"59","author":"N Rehman","year":"2011","unstructured":"Rehman, N., & Mandic, D.P. (2011). Filter bank property of multivariate empirical mode decomposition. IEEE Transactions on Signal Processing, 59(5), 2421\u20132426.","journal-title":"IEEE Transactions on Signal Processing"},{"key":"726_CR11","first-page":"485","volume":"4","author":"R Deering","year":"2005","unstructured":"Deering, R., Kaiser, J.F. (2005). The use of a masking signal to improve empirical mode decomposition. IEEE Acoustics, Speech and Signal Processing Proceedings, 4, 485\u2013488.","journal-title":"IEEE Acoustics, Speech and Signal Processing Proceedings"},{"issue":"1","key":"726_CR12","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1007\/s10827-007-0020-3","volume":"23","author":"CM Sweeney-Reed","year":"2007","unstructured":"Sweeney-Reed, C.M., & Nasuto, S.J. (2007). A novel approach to the detection of synchronisation in EEG based on empirical mode decomposition. Journal of Computational Neuroscience, 23(1), 79\u2013111.","journal-title":"Journal of Computational Neuroscience"},{"issue":"4","key":"726_CR13","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1109\/5.135376","volume":"80","author":"B Boashash","year":"1992","unstructured":"Boashash, B. (1992). Estimating and interpreting the instantaneous frequency of a signal - part 1: fundamentals. IEEE Proceedings, 80(4), 520\u2013538.","journal-title":"IEEE Proceedings"},{"issue":"4","key":"726_CR14","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1109\/5.135378","volume":"80","author":"B Boashash","year":"1992","unstructured":"Boashash, B. (1992). Estimating and interpreting the instantaneous frequency of a signal - part 2: algorithms and applications. IEEE Proceedings, 80(4), 540\u2013568.","journal-title":"IEEE Proceedings"},{"key":"726_CR15","doi-asserted-by":"crossref","unstructured":"Looney, D., & Mandic, D.P. (2008). A machine learning enhanced empirical mode decomposition. In IEEE acoustics, speech and signal processing proceedings (pp. 1897\u20131900).","DOI":"10.1109\/ICASSP.2008.4518005"},{"issue":"6","key":"726_CR16","doi-asserted-by":"crossref","first-page":"066705","DOI":"10.1103\/PhysRevE.79.066705","volume":"79","author":"S-L Lin","year":"2009","unstructured":"Lin, S.-L., Tung, P.-C., Huang N.E. (2009). Data analysis using a combination of independent component analysis and empirical mode decomposition. Physical Review E, 79(6), 066705.","journal-title":"Physical Review E"},{"issue":"4","key":"726_CR17","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1145\/321607.321609","volume":"17","author":"A Hiroshi","year":"1970","unstructured":"Hiroshi, A. (1970). A new method of interpolation and smooth curve fitting based on local procedures. Journal of the Association for Computing Machinery, 17(4), 589\u2013602.","journal-title":"Journal of the Association for Computing Machinery"},{"key":"726_CR18","author":"Y Wang","year":"2010","unstructured":"Wang, Y., He, Z., Zi, Y. (2010). A comparative study on the local mean decomposition and empirical mode decomposition and their applications to rotating machinery diagnosis. Journal of Vibration and Acoustics, 132(2). doi: 10.1115\/1.4000770 .","journal-title":"Journal of Vibration and Acoustics"},{"issue":"8","key":"726_CR19","doi-asserted-by":"crossref","first-page":"1941","DOI":"10.1016\/j.ymssp.2005.07.002","volume":"20","author":"S Qin","year":"2006","unstructured":"Qin, S., & Zhong, Y. (2006). A new envelope algorithm of Hilbert\u2013Huang transform. Mechanical Systems and Signal Processing, 20(8), 1941\u20131952.","journal-title":"Mechanical Systems and Signal Processing"},{"issue":"1","key":"726_CR20","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.measurement.2010.09.002","volume":"44","author":"L Lin","year":"2011","unstructured":"Lin, L., & Chu, F. (2011). Feature extraction of AE characteristics in offshore structure model using Hilbert\u2013Huang transform. Measurement, 44(1), 46\u201354.","journal-title":"Measurement"},{"key":"726_CR21","doi-asserted-by":"crossref","unstructured":"Shulin, L., Haifeng, Z., Hui, W., Rui, M. (2007). Application of improved EMD algorithm for the fault diagnosis of reciprocating pump valves with spring failure. In IEEE signal processing and its applications symposium.","DOI":"10.1109\/ISSPA.2007.4555473"},{"key":"726_CR22","doi-asserted-by":"crossref","unstructured":"Moler, C. (2004) Numerical Computing with MATLAB. http:\/\/www.mathworks.com\/moler\/index_ncm.html . Accessed 1 June 2010.","DOI":"10.1137\/1.9780898717952"},{"issue":"9","key":"726_CR23","doi-asserted-by":"crossref","first-page":"2600","DOI":"10.1109\/78.782222","volume":"47","author":"MS Lawrence","year":"1999","unstructured":"Lawrence, M.S. (1999). Computing the discrete-time \u201canalytic\u201d signal via FFT. IEEE Transactions on Signal Processing, 47(9), 2600\u20132603.","journal-title":"IEEE Transactions on Signal Processing"},{"issue":"6","key":"726_CR24","doi-asserted-by":"crossref","first-page":"061907","DOI":"10.1103\/PhysRevE.64.061907","volume":"64","author":"R Andrzejak","year":"2001","unstructured":"Andrzejak, R., Lehnertz, K., Rieke, C., Mormann, F., David, P., Elege, C. (2001). Indications of nonlinear deterministic and finite dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state. Phys. Rev. E, 64(6), 061907.","journal-title":"Phys. Rev. E"},{"key":"726_CR25","doi-asserted-by":"crossref","unstructured":"Stepien, R. (2011). New method for analysis of nonstationary signals. Nonlinear Biomedical Physics, 5(3).","DOI":"10.1186\/1753-4631-5-3"}],"container-title":["Journal of Signal Processing Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11265-012-0726-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11265-012-0726-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11265-012-0726-y","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,8]],"date-time":"2019-07-08T09:09:08Z","timestamp":1562576948000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11265-012-0726-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,1,19]]},"references-count":25,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2013,10]]}},"alternative-id":["726"],"URL":"https:\/\/doi.org\/10.1007\/s11265-012-0726-y","relation":{},"ISSN":["1939-8018","1939-8115"],"issn-type":[{"value":"1939-8018","type":"print"},{"value":"1939-8115","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,1,19]]}}}