[1] Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society of London Series A: Mathematical, Physical and Engineering Sciences, 1998, 454(1971): 903-995. DOI:10.1098/rspa.1998.0193.
[2] Huang N E, Shen Z, Long S R. A new view of nonlinear water waves: The Hilbert spectrum[J]. Annual Review of Fluid Mechanics, 1999, 31(1): 417-457. DOI:10.1146/annurev.fluid.31.1.417.
[3] Bi F R, Ma T, Wang X. Development of a novel knock characteristic detection method for gasoline engines based on wavelet-denoising and EMD decomposition[J].Mechanical Systems and Signal Processing, 2019, 117: 517-536. DOI:10.1016/j.ymssp.2018.08.008.
[4] Nie Z H, Shen F, Xu D J, et al. An EMD-SVR model for short-term prediction of ship motion using mirror symmetry and SVR algorithms to eliminate EMD boundary effect[J]. Ocean Engineering, 2020, 217: 107927. DOI:10.1016/j.oceaneng.2020.107927.
[5] Zhang X J, Huo Y, Wan D S. Improved EMD based on piecewise cubic hermite interpolation and mirror extension[J]. Chinese Journal of Electronics, 2020, 29(5): 899-905. DOI:10.1049/cje.2020.08.005.
[6] Yang J P, Li P Z, Yang Y F, et al. An improved EMD method for modal identification and a combined static-dynamic method for damage detection[J]. Journal of Sound and Vibration, 2018, 420: 242-260. DOI:10.1016/j.jsv.2018.01.036.
[7] Wang J, Liu W Y, Zhang S. An approach to eliminating end effects of EMD through mirror extension coupled with support vector machine method[J]. Personal and Ubiquitous Computing, 2019, 23(3/4): 443-452. DOI:10.1007/s00779-018-01198-6.
[8] Hao R J, Li F. A new method to suppress the EMD endpoint effect[J]. Journal of Vibration, Measurement and Diagnosis, 2018, 38(2): 341-345. DOI:10.16450/j.cnki.issn.1004-6801.2018.02.019. (in Chinese)
[9] Shao C X, Wang J, Fan J F, et al. A self adaptive method dealing with the end issue of EMD[J]. Acta Electtonica Sinica, 2007, 35(10): 1944-1948.(in Chinese)
[10] Su D L, Zheng H P. A boundary extension method for empirical mode decomposition end effect[J]. Journal of Aeronautics, 2016, 37(3): 960-969.(in Chinese)
[11] Xu Z F, Liu K. Method of empirical mode decomposition end effect based on analysis of extreme value symbol sequence[J]. Journal of Vibration, Measurement & Diagnosis, 2015, 35(2): 309-315.(in Chinese)
[12] Rong Q B. Research on EMD method for improving end effect and suppressing modal mixing [D]. Tianjin: Tianjin University, 2017.(in Chinese)
[13] Wald A. Sequential analysis[M]. New York: Wiley, 1947.
[14] Chen H X, Shang Y F, Sun K. Multiple fault condition recognition of gearbox with sequential hypothesis test[J].Mechanical Systems and Signal Processing, 2013, 40(2): 469-482. DOI:10.1016/j.ymssp.2013.06.023.
[15] Qian G B, Dong F, Wang S Y. Robust constrained minimum mixture kernel risk-sensitive loss algorithm for adaptive filtering[J].Digital Signal Processing, 2020, 107: 102859. DOI:10.1016/j.dsp.2020.102859.
[16] Zhu L F, Song C T, Pan L Z, et al. Adaptive filtering under the maximum correntropy criterion with variable center[J].IEEE Access, 2019, 7: 105902-105908. DOI:10.1109/ACCESS.2019.2932201.
[17] Li Y, Fang Z B, Wei Y F. Suppressing end effect of EMD based on local polynomial regression[J]. Journal of University of Science and Technology of China, 2014, 44(9): 786-792.(in Chinese)
[18] Huang N E, Wu M L C, Long S R, et al. A confidence limit for the empirical mode decomposition and Hilbert spectral analysis[J].Proceedings of the Royal Society of London Series A: Mathematical, Physical and Engineering Sciences, 2003, 459(2037): 2317-2345. DOI:10.1098/rspa.2003.1123.
[19] Han J P, Qian J, Dong X J. A method using mirror extension and RBF neural network to deal with end effect in EMD[J]. Journal of Vibration, Measurement & Diagnosis, 2010, 30(4): 414-417.(in Chinese)