for many decades, there has been a general perception in the literature that Fourier methods
are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we …

Adaptive empirical Fourier decomposition (AEFD) is a recently developed approach of
nonstationary signal mode separation. However, it requires to set the spectrum …

Empirical wavelet transform (EWT) is a novel method for analyzing the multi-component
signals and is proposed based on the classical wavelet transform. To fulfill an adaptive …

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of
traditional spectral analysis and to give a full informational representation of nonlinear and …

Empirical wavelet transform (EWT) is a new adaptive signal decomposition method based
on wavelet theory, the main idea is to establish an appropriate set of empirical wavelet filter …

Abstract The Holo-Hilbert spectral analysis (HHSA) is an emerging analysis tool for rotating
machinery fault diagnosis. It has an excellent performance in reflecting the cross-scale …

Differentiating normal from adventitious respiratory sounds (RS) is a major challenge in the
diagnosis of pulmonary diseases. Particularly, continuous adventitious sounds (CAS) are of …

Currently, empirical mode decomposition (EMD) has become a popular data-driven time-
frequency analysis method for nonstationary and nonlinear data. However, it is still limited to …

Abstract Background Ensemble Empirical Mode Decomposition (EEMD) has been
popularised for single-channel Electromyography (EMG) signal processing as it can …

Compared with wavelet analysis method of signal data, HHT (Hilbert-Huang Transform)
method is widely used for the local signal data analysis in the time–frequency domain …