Abstract
Numerous approaches have been explored to improve the performance of time–frequency analysis and to provide a sufficiently clear time–frequency representation. Among them, three methods such as the empirical mode decomposition (EMD) with Hilbert transform (HT) (or termed as the Hilbert–Huang Transform (HHT)), along with the Hilbert spectrum based on maximal overlap discrete wavelet package transform (MODWPT) and the multitaper time–frequency reassignment raised by Xiao and Flandrin, are noteworthy. This study evaluates the performances of three transforms mentioned above, in estimating single and multicomponent chip signals in the presence of noise or noise–free. Rényi Enropy is implemented for measuring the effectiveness of each algorithm. The paper demonstrates that under these conditions MODWPT owes better time–frequency resolution and statistical stability than the HHT. The multitaper time–frequency reassigned spectrogram makes excellent trade–off between time–frequency localization and local stationarity.
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Shan, PW., Li, M. (2010). A Study of Nonlinear Time–Varying Spectral Analysis Based on HHT, MODWPT and Multitaper Time–Frequency Reassignment. In: Taniar, D., Gervasi, O., Murgante, B., Pardede, E., Apduhan, B.O. (eds) Computational Science and Its Applications – ICCSA 2010. ICCSA 2010. Lecture Notes in Computer Science, vol 6017. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12165-4_16
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DOI: https://doi.org/10.1007/978-3-642-12165-4_16
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