References
[1]. Norden E. Huang, Z. Shen, & S. R. Long, M.L.Wu, E. H.
Shih, Q. Zheng, C. C. Tung, & H. H. Liu, (1998). “The
Empirical Mode Decomposition and the Hilbert Spectrum
for Nonlinear and Nonstationary Time Series Analysis,”
Proceedings of the Royal Society of London A, Vol. 454, pp
903-995.
[2]. Z. Wu & N. E. Huang, (2004). “A study of the
characteristics of white noise using the empirical mode decomposition method”. Proc. Roy. Soc London A, Vol.
460, pp. 1597-1611.
[3]. Z.K. Peng, Peter W. Tseb, & F.L. Chu. (2005). An
improved Hilbert–Huang transform and its application in
Vibration signal analysis. Journal of Sound and Vibration,
286 187–205
[4]. Dejie Yu, Junsheng Cheng, Yu Yang. (2010).
Application IEEE transactions on signal processing, Vol.
58, No. 3, March.
[5]. Empirical Mode Decomposition for Trivariate Signals
Naveed ur Rehman, Student Member, IEEE, and Danilo P.
Mandic, Senior Member, IEEE.
[6] Flandrin P, Rilling G, Goncalves P., “Empirical mode
decomposition as a filter bank”. IEEE Signal Processing
Letters, Feb. 2004, Vol. 11, Issue 2, Part 1, pp: 112–114.
[7]. N.E Huang, S.R.Long, & Z Shen, (1999). “A new view of
nonlinear water waves: The Hilbert spectrum”, Annu. Rev.
Fluid Mech, .Vol.31, pp. 417-457.
[8]. Wang Chun, & Peng Dong-ling, (2004). “The Hilbert-
Huang Transform and Its Application on Signal Denoising”,
China Journal of Scientific Instrument,
Vol.25,no.4, pp. 42-45.
[9]. R. Gabriel & F. Patrick. (2008). “The Empirical Mode
Decomposition Answers”. IEEE Transactions on Signal Processing, Vol. 56, No. 1.
[10]. Z. K. Penga, Peter W. Tse, & F. L. Chu, (2005). “A
comparison study of improved Hilbert–Huang transform
and wavelet transform: Application to fault diagnosis for
rolling bearing,” Mechanical Systems and Signal
Processing, pp. 974–988.
[11]. Yuan Li. (2001). ”Wavelet Analysis for Change Points
and Nonlinear Wavelet Estimates in Time Series.” Beijing:
China Statistics Press.
[12]. Angkoon Phinyomark, Chusak Limsakul, & Pornchai
Phukpattaranont (2010). “Optimal Wavelet Functions in
Wavelet Denoising for Multifunction Myoelectric Control”
“IEEE Transactions on Signal Processing.
[13]. H. G. R. Tan, A. C. Tan, P. Y. Khong, & V. H. Mok, (2007).
“Best wavelet function identification system for ecg signal
denoise applications,” in International Conference on
Intelligent and Advanced Systems, pp. 631–634.
[14]. M. Kania, M. Fereniec, & R. Maniewski, (2007).
“Wavelet denoising for multi-lead high resolution ecg
signals,” Measurement Science Review, Vol. 7, No. 4, pp.
30–33,
[15]. S. Neville & N. Dimopoulos, (2006). “Wavelet
denoising of coarsely quantized signals,” IEEE Transactions
on Instrumentation and Measurement, Vol. 55, No. 3, pp.
892–901.
