An iterative filtering method for adaptive signal decomposition based on a PDE model

Series: 
Applied and Computational Mathematics Seminar
Monday, November 7, 2011 - 14:00
30 minutes
Location: 
Skiles 006
,  
GT Math
Organizer: 
The empirical mode decomposition (EMD) was a method developed by Huang et al as an alternative approach to the traditional Fourier and wavelet techniques for studying signals. It decomposes  signals into finite numbers of components which have well behaved intataneous frequency via Hilbert transform. These components are called intrinstic mode function (IMF).  Recently, alternative algorithms for EMD have been developed, such as iterative filtering method or sparse time-frequency representation by optimization. In this talk we present our recent progress on iterative filtering method. We develop a new local filter based on a partial differential equation (PDE) model as well as a new  approach to compute the instantaneous frequency, which generate similar or  better results than the traditional EMD algorithm.