Hilbert-huang transform based time-frequency distribution and comparisons with other three

Authors:
Ming Li;Xue-Kang Gu;Shen-Shen Yang
Affiliations:
School of Information Science & Technology, East China Normal University, Shanghai, P.R. China;China Ship Scientific Center, Wuxi, P.R. China;School of Information Science & Technology, East China Normal University, Shanghai, P.R. China
Venue:
IMACS'08 Proceedings of the 7th WSEAS International Conference on Instrumentation, Measurement, Circuits and Systems
Year:
2008

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Abstract

Time-frequency distribution (TFD) of signals gains increasing applications in various areas of sciences and engineering for processing non-stationary signals and nonlinear signals. Traditional methods in the field are short-time Fourier transform (STFT), generalized TFDs in the Cohen class (GTFD), and wavelet transform (WT) based TFD. Recently, Huang et al. introduced a new method called Hilbert-Huang transform (HHT). This is an adaptively data-driven approach without the limitations caused by various window functions for STFT, different kernels for GTFD, and different mother functions for WT. This paper discusses four types of TFDs with demonstrations, providing a case to show that HHT based TFD may have high resolution.