{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T01:17:57Z","timestamp":1768439877272,"version":"3.49.0"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2020,9,10]],"date-time":"2020-09-10T00:00:00Z","timestamp":1599696000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,9,10]],"date-time":"2020-09-10T00:00:00Z","timestamp":1599696000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100006464","name":"Birla Institute of Technology and Science, Pilani","doi-asserted-by":"publisher","award":["FR\/SCM\/150618\/EEE"],"award-info":[{"award-number":["FR\/SCM\/150618\/EEE"]}],"id":[{"id":"10.13039\/501100006464","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Circuits Syst Signal Process"],"published-print":{"date-parts":[[2021,3]]},"DOI":"10.1007\/s00034-020-01537-0","type":"journal-article","created":{"date-parts":[[2020,9,10]],"date-time":"2020-09-10T18:51:56Z","timestamp":1599763916000},"page":"1207-1232","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Sliding Mode Singular Spectrum Analysis for the Elimination of Cross-Terms in Wigner\u2013Ville Distribution"],"prefix":"10.1007","volume":"40","author":[{"given":"Rohan","family":"Panda","sequence":"first","affiliation":[]},{"given":"Sahil","family":"Jain","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2517-3103","authenticated-orcid":false,"given":"R. K.","family":"Tripathy","sequence":"additional","affiliation":[]},{"given":"Rishi Raj","family":"Sharma","sequence":"additional","affiliation":[]},{"given":"Ram Bilas","family":"Pachori","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,10]]},"reference":[{"issue":"4","key":"1537_CR1","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1109\/TASLP.2016.2526779","volume":"24","author":"KT Andersen","year":"2016","unstructured":"K.T. Andersen, M. Moonen, Adaptive time-frequency analysis for noise reduction in an audio filter bank with low delay. IEEE\/ACM Trans. Audio Speech Lang. Process. 24(4), 784\u2013795 (2016)","journal-title":"IEEE\/ACM Trans. Audio Speech Lang. Process."},{"key":"1537_CR2","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.sigpro.2016.09.004","volume":"132","author":"GK Apostolidis","year":"2017","unstructured":"G.K. Apostolidis, L.J. Hadjileontiadis, Swarm decomposition: a novel signal analysis using swarm intelligence. Signal Process. 132, 40\u201350 (2017)","journal-title":"Signal Process."},{"key":"1537_CR3","volume-title":"Time-Frequency Signal Analysis and Processing: A Comprehensive Reference","author":"B Boashash","year":"2003","unstructured":"B. Boashash, Time-Frequency Signal Analysis and Processing: A Comprehensive Reference (Elsevier, Amsterdam, 2003)"},{"issue":"4","key":"1537_CR4","doi-asserted-by":"crossref","first-page":"1391","DOI":"10.1109\/18.923723","volume":"47","author":"RG Baraniuk","year":"2001","unstructured":"R.G. Baraniuk, P. Flandrin, A.J. Janssen, O.J. Michel, Measuring time-frequency information content using the R\u00e9nyi entropies. IEEE Trans. Inf. Theory 47(4), 1391\u20131409 (2001)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"1537_CR5","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.1006\/mssp.2000.1338","volume":"15","author":"N Baydar","year":"2001","unstructured":"N. Baydar, A. Ball, A comparative study of acoustic and vibration signals in detection of gear failures using Wigner\u2013Ville distribution. Mech. Syst. Signal Process. 15, 1091\u20131107 (2001)","journal-title":"Mech. Syst. Signal Process."},{"key":"1537_CR6","doi-asserted-by":"crossref","unstructured":"M. Bayram, R.G. Baraniuk, Multiple window time-frequency analysis, in Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96) (IEEE, 1996), pp. 173\u2013176","DOI":"10.1117\/12.255431"},{"key":"1537_CR7","volume-title":"Time-Frequency Signal Analysis and Processing: A Comprehensive Reference","author":"B Boashash","year":"2015","unstructured":"B. Boashash, Time-Frequency Signal Analysis and Processing: A Comprehensive Reference (Academic Press, Cambridge, 2015)"},{"issue":"s1","key":"1537_CR8","first-page":"317","volume":"40","author":"R Bousseljot","year":"1995","unstructured":"R. Bousseljot, D. Kreiseler, A. Schnabel, Nutzung der ekg-signaldatenbank cardiodat der ptb \u00fcber das internet. Biomedizinische Technik\/Biomed. Eng. 40(s1), 317\u2013318 (1995)","journal-title":"Biomedizinische Technik\/Biomed. Eng."},{"key":"1537_CR9","doi-asserted-by":"crossref","unstructured":"Y. Chai, X. Zhang, EMD-WVD time-frequency distribution for analysis of multi-component signals, in Fourth International Conference on Wireless and Optical Communications, vol. 9902 (International Society for Optics and Photonics, 2016), p. 99020W","DOI":"10.1117\/12.2262260"},{"key":"1537_CR10","volume-title":"Time-Frequency Transforms for Radar Imaging and Signal Analysis","author":"VC Chen","year":"2001","unstructured":"V.C. Chen, H. Ling, Time-Frequency Transforms for Radar Imaging and Signal Analysis (Artech House, Boston, 2001)"},{"issue":"1","key":"1537_CR11","first-page":"494","volume":"25","author":"SH Cho","year":"2009","unstructured":"S.H. Cho, G. Jang, S.H. Kwon, Time-frequency analysis of power-quality disturbances via the Gabor\u2013Wigner transform. IEEE Trans. Power Deliv. 25(1), 494\u2013499 (2009)","journal-title":"IEEE Trans. Power Deliv."},{"issue":"6","key":"1537_CR12","doi-asserted-by":"crossref","first-page":"862","DOI":"10.1109\/ASSP.1989.28057","volume":"37","author":"HI Choi","year":"1989","unstructured":"H.I. Choi, W.J. Williams, Improved time-frequency representation of multicomponent signals using exponential kernels. IEEE Trans. Acoust. Speech Signal Process. 37(6), 862\u2013871 (1989)","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"issue":"4","key":"1537_CR13","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1109\/TAU.1970.1162139","volume":"18","author":"V Cizek","year":"1970","unstructured":"V. Cizek, Discrete Hilbert transform. IEEE Trans. Audio Electroacoust. 18(4), 340\u2013343 (1970)","journal-title":"IEEE Trans. Audio Electroacoust."},{"issue":"3","key":"1537_CR14","first-page":"217","volume":"35","author":"T Claasen","year":"1980","unstructured":"T. Claasen, W. Mecklenbrauker, The Wigner distribution\u2014A tool for time-frequency signal analysis. Philips J. Res. 35(3), 217\u2013250 (1980)","journal-title":"Philips J. Res."},{"issue":"8","key":"1537_CR15","doi-asserted-by":"crossref","first-page":"4217","DOI":"10.1109\/TIE.2013.2286581","volume":"61","author":"V Climente-Alarcon","year":"2013","unstructured":"V. Climente-Alarcon, J.A. Antonino-Daviu, M. Riera-Guasp, M. Vlcek, Induction motor diagnosis by advanced notch FIR filters and the Wigner\u2013Ville distribution. IEEE Trans. Ind. Electron. 61(8), 4217\u20134227 (2013)","journal-title":"IEEE Trans. Ind. Electron."},{"issue":"2","key":"1537_CR16","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1109\/TPWRD.2003.809616","volume":"18","author":"P Dash","year":"2003","unstructured":"P. Dash, B. Panigrahi, G. Panda, Power quality analysis using s-transform. IEEE Trans. Power Deliv. 18(2), 406\u2013411 (2003)","journal-title":"IEEE Trans. Power Deliv."},{"key":"1537_CR17","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/j.jsv.2016.07.004","volume":"382","author":"Y Ding","year":"2016","unstructured":"Y. Ding, W. He, B. Chen, Y. Zi, I.W. Selesnick, Detection of faults in rotating machinery using periodic time-frequency sparsity. J. Sound Vib. 382, 357\u2013378 (2016)","journal-title":"J. Sound Vib."},{"key":"1537_CR18","unstructured":"P. Flandrin, O. Rioul, Affine smoothing of the Wigner\u2013Ville distribution, in International Conference on Acoustics, Speech, and Signal Processing (IEEE, 1990), pp. 2455\u20132458"},{"key":"1537_CR19","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1016\/j.cmpb.2013.11.018","volume":"113","author":"A Gavrovska","year":"2014","unstructured":"A. Gavrovska, V. Bogdanovi\u0107, I. Reljin, B. Reljin, Automatic heart sound detection in pediatric patients without electrocardiogram reference via pseudo-affine Wigner\u2013Ville distribution and Haar wavelet lifting. Comput. Methods Programs Biomed. 113, 515\u2013528 (2014)","journal-title":"Comput. Methods Programs Biomed."},{"issue":"23","key":"1537_CR20","doi-asserted-by":"crossref","first-page":"e215","DOI":"10.1161\/01.CIR.101.23.e215","volume":"101","author":"AL Goldberger","year":"2000","unstructured":"A.L. Goldberger, L.A. Amaral, L. Glass, J.M. Hausdorff, P.C. Ivanov, R.G. Mark, J.E. Mietus, G.B. Moody, C.K. Peng, H.E. Stanley, Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals. Circulation 101(23), e215\u2013e220 (2000)","journal-title":"Circulation"},{"key":"1537_CR21","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-34913-3","volume-title":"Singular Spectrum Analysis for Time Series","author":"N Golyandina","year":"2013","unstructured":"N. Golyandina, A. Zhigljavsky, Singular Spectrum Analysis for Time Series (Springer, Berlin, 2013)"},{"issue":"2","key":"1537_CR22","doi-asserted-by":"crossref","first-page":"O9","DOI":"10.1190\/geo2012-0199.1","volume":"78","author":"J Han","year":"2013","unstructured":"J. Han, M. van der Baan, Empirical mode decomposition for seismic time-frequency analysis. Geophysics 78(2), O9\u2013O19 (2013)","journal-title":"Geophysics"},{"key":"1537_CR23","doi-asserted-by":"crossref","first-page":"1304","DOI":"10.1109\/LGRS.2019.2894223","volume":"16","author":"G Hao","year":"2019","unstructured":"G. Hao, F. Tan, X. Hu, Y. Bai, Y. Lv, A matching pursuit-based method for cross-term suppression in WVD and its application to the ENPEMF. IEEE Geosci. Remote Sens. Lett. 16, 1304\u20131308 (2019)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"1","key":"1537_CR24","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1109\/TSP.2017.2752720","volume":"66","author":"J Harmouche","year":"2018","unstructured":"J. Harmouche, D. Fourer, F. Auger, P. Borgnat, P. Flandrin, The sliding singular spectrum analysis: a data-driven nonstationary signal decomposition tool. IEEE Trans. Signal Process. 66(1), 131\u2013136 (2018). https:\/\/doi.org\/10.1109\/TSP.2017.2752720","journal-title":"IEEE Trans. Signal Process."},{"key":"1537_CR25","doi-asserted-by":"crossref","unstructured":"N.E. Huang, Z. Shen, S.R. Long, M.C. Wu, H.H. Shih, Q. Zheng, N.C. Yen, C.C. Tung, H.H. Liu, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, in Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, vol. 454 (The Royal Society, 1998), pp. 903\u2013995","DOI":"10.1098\/rspa.1998.0193"},{"issue":"6","key":"1537_CR26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LSENS.2020.2996096","volume":"4","author":"S Jain","year":"2020","unstructured":"S. Jain, R. Panda, R.K. Tripathy, Multivariate sliding mode singular spectrum analysis for the decomposition of multisensor timeserie. IEEE Sens. Lett. 4(6), 1\u20134 (2020)","journal-title":"IEEE Sens. Lett."},{"issue":"12\u201315","key":"1537_CR27","doi-asserted-by":"crossref","first-page":"1435","DOI":"10.1016\/S0167-6105(02)00263-5","volume":"90","author":"A Kareem","year":"2002","unstructured":"A. Kareem, T. Kijewski, Time-frequency analysis of wind effects on structures. J. Wind Eng. Ind. Aerodyn. 90(12\u201315), 1435\u20131452 (2002)","journal-title":"J. Wind Eng. Ind. Aerodyn."},{"key":"1537_CR28","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.sigpro.2016.02.027","volume":"127","author":"NA Khan","year":"2016","unstructured":"N.A. Khan, M. Sandsten, Time-frequency image enhancement based on interference suppression in Wigner\u2013Ville distribution. Signal Process. 127, 80\u201385 (2016)","journal-title":"Signal Process."},{"issue":"3","key":"1537_CR29","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1016\/j.sigpro.2010.06.004","volume":"91","author":"NA Khan","year":"2011","unstructured":"N.A. Khan, I.A. Taj, M.N. Jaffri, S. Ijaz, Cross-term elimination in Wigner distribution based on 2D signal processing techniques. Signal Process. 91(3), 590\u2013599 (2011)","journal-title":"Signal Process."},{"key":"1537_CR30","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1016\/j.ymssp.2018.06.055","volume":"116","author":"F Li","year":"2019","unstructured":"F. Li, R. Li, L. Tian, L. Chen, J. Liu, Data-driven time-frequency analysis method based on variational mode decomposition and its application to gear fault diagnosis in variable working conditions. Mech. Syst. Signal Process. 116, 462\u2013479 (2019)","journal-title":"Mech. Syst. Signal Process."},{"key":"1537_CR31","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.neucom.2015.04.128","volume":"195","author":"Y Li","year":"2016","unstructured":"Y. Li, Q. Liu, S.R. Tan, R.H. Chan, High-resolution time-frequency analysis of eeg signals using multiscale radial basis functions. Neurocomputing 195, 96\u2013103 (2016)","journal-title":"Neurocomputing"},{"key":"1537_CR32","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.neucom.2016.01.062","volume":"193","author":"Y Li","year":"2016","unstructured":"Y. Li, M.L. Luo, K. Li, A multiwavelet-based time-varying model identification approach for time-frequency analysis of EEG signals. Neurocomputing 193, 106\u2013114 (2016)","journal-title":"Neurocomputing"},{"issue":"1","key":"1537_CR33","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1109\/LGRS.2016.2630734","volume":"14","author":"N Liu","year":"2016","unstructured":"N. Liu, J. Gao, X. Jiang, Z. Zhang, Q. Wang, Seismic time-frequency analysis via STFT-based concentration of frequency and time. IEEE Geosci. Remote Sens. Lett. 14(1), 127\u2013131 (2016)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"6","key":"1537_CR34","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1109\/MSP.2013.2267931","volume":"30","author":"DP Mandic","year":"2013","unstructured":"D.P. Mandic, N. ur Rehman, Z. Wu, N.E. Huang, Empirical mode decomposition-based time-frequency analysis of multivariate signals: the power of adaptive data analysis. IEEE Signal Process. Mag. 30(6), 74\u201386 (2013)","journal-title":"IEEE Signal Process. Mag."},{"key":"1537_CR35","volume-title":"Wavelets and Operators","author":"Y Meyer","year":"1992","unstructured":"Y. Meyer, Wavelets and Operators, vol. 1 (Cambridge University Press, Cambridge, 1992)"},{"key":"1537_CR36","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.sigpro.2015.07.026","volume":"120","author":"RB Pachori","year":"2016","unstructured":"R.B. Pachori, A. Nishad, Cross-terms reduction in the Wigner\u2013Ville distribution using tunable-q wavelet transform. Signal Process. 120, 288\u2013304 (2016)","journal-title":"Signal Process."},{"issue":"2","key":"1537_CR37","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1016\/j.dsp.2006.10.004","volume":"17","author":"RB Pachori","year":"2007","unstructured":"R.B. Pachori, P. Sircar, A new technique to reduce cross terms in the Wigner distribution. Digit. Signal Process. 17(2), 466\u2013474 (2007)","journal-title":"Digit. Signal Process."},{"issue":"1","key":"1537_CR38","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1190\/1.1543223","volume":"68","author":"CR Pinnegar","year":"2003","unstructured":"C.R. Pinnegar, L. Mansinha, The s-transform with windows of arbitrary and varying shape. Geophysics 68(1), 381\u2013385 (2003)","journal-title":"Geophysics"},{"issue":"1","key":"1537_CR39","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/s11760-014-0713-9","volume":"10","author":"H Ren","year":"2016","unstructured":"H. Ren, A. Ren, Z. Li, A new strategy for the suppression of cross-terms in pseudo Wigner\u2013Ville distribution. SIViP 10(1), 139\u2013144 (2016)","journal-title":"SIViP"},{"issue":"2","key":"1537_CR40","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1109\/TBME.2011.2173936","volume":"59","author":"S Sanei","year":"2011","unstructured":"S. Sanei, T.K. Lee, V. Abolghasemi, A new adaptive line enhancer based on singular spectrum analysis. IEEE Trans. Biomed. Eng. 59(2), 428\u2013434 (2011)","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"16","key":"1537_CR41","doi-asserted-by":"crossref","first-page":"3187","DOI":"10.1029\/2000GL012698","volume":"28","author":"DH Schoellhamer","year":"2001","unstructured":"D.H. Schoellhamer, Singular spectrum analysis for time series with missing data. Geophys. Res. Lett. 28(16), 3187\u20133190 (2001)","journal-title":"Geophys. Res. Lett."},{"key":"1537_CR42","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1109\/LSP.2008.917014","volume":"15","author":"E Sejdic","year":"2008","unstructured":"E. Sejdic, L. Stankovic, M. Dakovic, J. Jiang, Instantaneous frequency estimation using the s-transform. IEEE Signal Process. Lett. 15, 309\u2013312 (2008)","journal-title":"IEEE Signal Process. Lett."},{"key":"1537_CR43","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1007\/s11760-019-01549-7","volume":"14","author":"RR Sharma","year":"2019","unstructured":"R.R. Sharma, A. Kalyani, R.B. Pachori, An empirical wavelet transform-based approach for cross-terms-free Wigner\u2013Ville distribution. Signal Image Video Process. 14, 249\u2013256 (2019). https:\/\/doi.org\/10.1007\/s11760-019-01549-7","journal-title":"Signal Image Video Process."},{"key":"1537_CR44","doi-asserted-by":"crossref","unstructured":"R.R. Sharma, P. Meena, R.B. Pachori, Enhanced time-frequency representation based on variational mode decomposition and Wigner\u2013Ville distribution, in Recent Trends in Image and Signal Processing in Computer Vision (Springer, 2020), pp. 265\u2013284","DOI":"10.1007\/978-981-15-2740-1_18"},{"key":"1537_CR45","doi-asserted-by":"publisher","first-page":"3330","DOI":"10.1007\/s00034-018-0846-0","volume":"37","author":"RR Sharma","year":"2018","unstructured":"R.R. Sharma, R. Pachori, Improved eigenvalue decomposition-based approach for reducing cross-terms in Wigner\u2013Ville distribution. Circuits Syst. Signal Process. 37, 3330\u20133350 (2018). https:\/\/doi.org\/10.1007\/s00034-018-0846-0","journal-title":"Circuits Syst. Signal Process."},{"key":"1537_CR46","doi-asserted-by":"crossref","first-page":"102796","DOI":"10.1016\/j.dsp.2020.102796","volume":"104","author":"H Singh","year":"2020","unstructured":"H. Singh, R.K. Tripathy, R.B. Pachori, Detection of sleep apnea from heart beat interval and ECG derived respiration signals using sliding mode singular spectrum analysis. Digit. Signal Process. 104, 102796 (2020)","journal-title":"Digit. Signal Process."},{"issue":"3","key":"1537_CR47","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/S0165-1684(97)00009-1","volume":"57","author":"P Sircar","year":"1997","unstructured":"P. Sircar, S. Sharma, Complex FM signal model for non-stationary signals. Signal Process. 57(3), 283\u2013304 (1997)","journal-title":"Signal Process."},{"issue":"3","key":"1537_CR48","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1016\/S0165-1684(00)00236-X","volume":"81","author":"L Stankovi\u0107","year":"2001","unstructured":"L. Stankovi\u0107, A measure of some time-frequency distributions concentration. Signal Process. 81(3), 621\u2013631 (2001)","journal-title":"Signal Process."},{"key":"1537_CR49","volume-title":"Time-Frequency Signal Analysis with Applications","author":"L Stankovic","year":"2013","unstructured":"L. Stankovic, M. Dakovi\u0107, T. Thayaparan, Time-Frequency Signal Analysis with Applications (Artech House, Boston, 2013)"},{"issue":"4","key":"1537_CR50","doi-asserted-by":"crossref","first-page":"998","DOI":"10.1109\/78.492555","volume":"44","author":"RG Stockwell","year":"1996","unstructured":"R.G. Stockwell, L. Mansinha, R. Lowe, Localization of the complex spectrum: the s transform. IEEE Trans. Signal Process. 44(4), 998\u20131001 (1996)","journal-title":"IEEE Trans. Signal Process."},{"issue":"07","key":"1537_CR51","doi-asserted-by":"crossref","first-page":"1740044","DOI":"10.1142\/S0219519417400449","volume":"17","author":"R Tripathy","year":"2017","unstructured":"R. Tripathy, M.R.A. Paternina, J.G. Arrieta, P. Pattanaik, Automated detection of atrial fibrillation ECG signals using two stage VMD and atrial fibrillation diagnosis index. J. Mech. Med. Biol. 17(07), 1740044 (2017)","journal-title":"J. Mech. Med. Biol."},{"issue":"4","key":"1537_CR52","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1007\/s10916-016-0441-5","volume":"40","author":"R Tripathy","year":"2016","unstructured":"R. Tripathy, L. Sharma, S. Dandapat, Detection of shockable ventricular arrhythmia using variational mode decomposition. J. Med. Syst. 40(4), 79 (2016)","journal-title":"J. Med. Syst."},{"key":"1537_CR53","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.cmpb.2019.03.008","volume":"173","author":"RK Tripathy","year":"2019","unstructured":"R.K. Tripathy, M.R. Paternina, J.G. Arrieta, A. Zamora-M\u00e9ndez, G.R. Naik, Automated detection of congestive heart failure from electrocardiogram signal using stockwell transform and hybrid classification scheme. Comput. Methods Programs Biomed. 173, 53\u201365 (2019)","journal-title":"Comput. Methods Programs Biomed."},{"issue":"2","key":"1537_CR54","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/0165-1684(91)90133-4","volume":"24","author":"D Waldo","year":"1991","unstructured":"D. Waldo, P.R. Chitrapu, On the Wigner Ville distribution of finite duration signals. Signal Process. 24(2), 231\u2013237 (1991)","journal-title":"Signal Process."},{"issue":"4","key":"1537_CR55","doi-asserted-by":"crossref","first-page":"354","DOI":"10.3390\/e21040354","volume":"21","author":"S Wan","year":"2019","unstructured":"S. Wan, B. Peng, An integrated approach based on swarm decomposition, morphology envelope dispersion entropy, and random forest for multi-fault recognition of rolling bearing. Entropy 21(4), 354 (2019)","journal-title":"Entropy"},{"key":"1537_CR56","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.ymssp.2017.09.042","volume":"103","author":"L Wang","year":"2018","unstructured":"L. Wang, Z. Liu, Q. Miao, X. Zhang, Time-frequency analysis based on ensemble local mean decomposition and fast kurtogram for rotating machinery fault diagnosis. Mech. Syst. Signal Process. 103, 60\u201375 (2018)","journal-title":"Mech. Syst. Signal Process."},{"issue":"4","key":"1537_CR57","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1049\/iet-rpg.2016.0088","volume":"11","author":"W Yang","year":"2016","unstructured":"W. Yang, Z. Peng, K. Wei, P. Shi, W. Tian, Superiorities of variational mode decomposition over empirical mode decomposition particularly in time-frequency feature extraction and wind turbine condition monitoring. IET Renew. Power Gener. 11(4), 443\u2013452 (2016)","journal-title":"IET Renew. Power Gener."}],"container-title":["Circuits, Systems, and Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00034-020-01537-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00034-020-01537-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00034-020-01537-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,9]],"date-time":"2021-09-09T23:34:01Z","timestamp":1631230441000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00034-020-01537-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,10]]},"references-count":57,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,3]]}},"alternative-id":["1537"],"URL":"https:\/\/doi.org\/10.1007\/s00034-020-01537-0","relation":{},"ISSN":["0278-081X","1531-5878"],"issn-type":[{"value":"0278-081X","type":"print"},{"value":"1531-5878","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,10]]},"assertion":[{"value":"19 November 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 August 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 August 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 September 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}