Empirical Mode Decomposition
Group Members: Max Lambert, Andrew Engroff, Matt Dyer, Ben Byer

   Synthetic vs. Natural
   MATLAB Code

  • The EMD will break down a signal into its component IMFs.
  • An IMF is a function that:
    1. has only one extreme between zero crossings, and
    2. has a mean value of zero.
  • In order to describe the process, we borrow from our poster the following section:
The Sifting Process
  • The sifting process is what EMD uses to decomposes the signal into IMFs.
    The sifting process is as follows:
    For a signal X(t), let m1 be the mean of its upper and lower envelopes as determined from a cubic-spline interpolation of local maxima and minima. The locality is determined by an arbitrary parameter; the calculation time and the effectiveness of the EMD depends greatly on such a parameter.
  • The first component h1 is computed:
  • In the second sifting process, h1 is treated as the data, and m11 is the mean of h1ís upper and lower envelopes:
  • This sifting procedure is repeated k times, until h1k is an IMF, that is:
  • Then it is designated as c1=h1k, the first IMF component from the data, which contains the shortest period component of the signal. We separate it from the rest of the data: X(t)-c1 = r1 The procedure is repeated on rj: r1-c2 = r2,....,rn-1 - cn = rn