@article{(Open Science Index):https://publications.waset.org/pdf/10007433,
	  title     = {Optimizing Approach for Sifting Process to Solve a Common Type of Empirical Mode Decomposition Mode Mixing},
	  author    = {Saad Al-Baddai and  Karema Al-Subari and  Elmar Lang and  Bernd Ludwig},
	  country	= {},
	  institution	= {},
	  abstract     = {Empirical mode decomposition (EMD), a new
data-driven of time-series decomposition, has the advantage of
supposing that a time series is non-linear or non-stationary, as
is implicitly achieved in Fourier decomposition. However, the
EMD suffers of mode mixing problem in some cases. The aim of
this paper is to present a solution for a common type of signals
causing of EMD mode mixing problem, in case a signal suffers
of an intermittency. By an artificial example, the solution shows
superior performance in terms of cope EMD mode mixing problem
comparing with the conventional EMD and Ensemble Empirical
Mode decomposition (EEMD). Furthermore, the over-sifting problem
is also completely avoided; and computation load is reduced roughly
six times compared with EEMD, an ensemble number of 50.},
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {11},
	  number    = {6},
	  year      = {2017},
	  pages     = {717 - 725},
	  ee        = {https://publications.waset.org/pdf/10007433},
	  url   	= {https://publications.waset.org/vol/126},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 126, 2017},