ABSTRACT
Hilbert-Huang transform (HHT) is the designated name for the result of empirical mode decomposition (EMD) and the Hilbert spectral analysis (HSA) methods, which were both introduced recently by Huang et al. (1996, 1998, 1999, and 2003), specifically for analyzing data from nonlinear and nonstationary processes. Data analysis is an indispensable step in understanding the physical processes, but traditionally the data analysis methods were dominated by Fourier-based analysis. The problems of such an approach were discussed in detail by Huang et al. (1998). As data analysis is important for both theoretical and experimental studies (for data is the only real link between theory and reality), we desperately need new methods in order to gain a deeper insight into the underlying processes that actually generate the data. The method we really need should not be limited to linear and stationary processes, and it should yield physically meaningful results.
