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Multiple-view time–frequency distribution based on the empirical mode decomposition

Multiple-view time–frequency distribution based on the empirical mode decomposition

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This study proposes a novel, composite time–frequency distribution (TFD) constructed using a multiple-view approach. This composite TFD utilises the intrinsic mode functions (IMFs) of the empirical mode decomposition (EMD) to generate each view that are then combined using the arithmetic mean. This process has the potential to eliminate the inter-component interference generated by a quadratic TFD (QTFD), as the IMFs of the EMD are, in general, monocomponent signals. The formulation of the multiple-view TFD in the ambiguity domain results in faster computation, compared to a convolutive implementation in the time–frequency domain, and a more robust TFD in the presence of noise. The composite TFD, referred to as the EMD-TFD, was shown to generate a heuristically more accurate representation of the distribution of time–frequency energy in a signal. It was also shown to have performance comparable to the Wigner–Ville distribution when estimating the instantaneous frequency of multiple signal components in the presence of noise.

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