Filter-based Empirical Mode Decomposition and Its Application to Filter Bank Design
Date Issued
2012
Date
2012
Author(s)
Chang, Che-Shuo
Abstract
The empirical mode decomposition (EMD) has been widely applied to many research fields for decomposing the signal. The algorithm is based on the spline interpolation of local extreme points. This procedure makes it difficult to analyze the performance and the corresponding mathematical properties. Thus till now most of knowledges about EMD are based on practical observations. In addition, the EMD itself has little flexibility to adapt to different requirement. In this work, the proposed filter-based empirical mode decomposition (FB-EMD) provides a parametrized algorithm adjustable for different settings. In this way it is possible to change the decreasing rate of the cutoff frequency of the intrinsic mode function (IMF). Moreover, the equivalent filter bank and the decomposition results are predictable and controllable. This enables us to apply the FB-EMD to the filter bank design. Another feature of the FB-EMD is that the algorithm is resistant to the noise and intermittencies. While being free from the boundary process and the mode mixing problem, the proposed method is also efficient. The numerical results show that in general the FB-EMD have better performance in real signals and autoregressive moving-average signals. The spectral overlap is also reduced. These discussions and the numerical results is helpful for developing a theoretic framework for the EMD based algorithm.
Subjects
empirical mode decomposition
trend signal
interpolation
non-stationary signal
Type
thesis
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