The aim of this paper was to compare empirical mode decomposition (EMD) and two new extended methods of EMD named complex empirical mode decomposition (complex-EMD) and bivariate empirical mode decomposition (bivariate-EMD). All methods were used to analyze stabilogram center of pressure (COP) time series. The two new methods are suitable to be applied to complex time series to extract complex ...

A new method for analysis of electroencephalogram (EEG) signals using Empirical Mode Decomposition (EMD) and Fourier-Bessel (FB) expansion has been presented in this paper. The EMD decomposes a EEG signal into a finite set of band-limited signals termed Intrinsic Mode Functions (IMFs). The mean frequency (MF) for each IMF has been computed using FB expansion. The MF measure of the IMFs has been...

The empirical mode decomposition (EMD) was a method pioneered by Huang et al [8] as an alternative technique to the traditional Fourier and wavelet techniques for studying signals. It decomposes a signal into several components called intrinsic mode functions (IMF), which have shown to admit better behaved instantaneous frequencies via Hilbert transforms. In this paper we propose an alternative...

Voice stress analysis (VSA) is accomplished by measuring fluctuations in the physiological microtremor present in speech. In this paper, Empirical Mode Decomposition is compared to traditional Fast Fourier Transform in the analysis of the physiological microtremor. The results are expected to show that EMD is better suited in the detection of stress in voice.

Voltage fluctuation is an essential problem exiting in distribution network. This paper applies Hilbert Huang transform (HHT) algorithm to dealing with voltage fluctuation tracking. An adaptive method based on waveform matching is presented to prevent the endpoint effects in mode decomposition. Numerical examples are given and the simulation verifies the practicality of the proposed method.

Cantonese is a very popular spoken language/dialect, which is well known for its rich set of nine tones and the similarity in tone contours between its tones. Automated tone recognition of Cantonese is very challenging. Hilbert-Huang Transform (HHT) is an empirical algorithm that works on non-stationary and nonlinear signals. In this study, the performance of the HHT algorithm on the recognitio...

BACKGROUND Heatwaves could cause the population excess death numbers to be ranged from tens to thousands within a couple of weeks in a local area. An excess mortality due to a special event (e.g., a heatwave or an epidemic outbreak) is estimated by subtracting the mortality figure under 'normal' conditions from the historical daily mortality records. The calculation of the excess mortality is a...

This paper presents the findings of an investigation into Partial Discharge signal denoising using techniques based on Empirical Mode Decomposition. The denoising techniques are based on thresholding the Intrinsic Mode Functions which result from the Empirical Mode Decomposition of a signal. The results of the tests carried out show clearly that these techniques can produce excellent results wh...

Time-frequency analysis plays a significant role in seismic data processing and interpretation. Complete ensemble empirical mode decomposition decomposes a seismic signal into a sum of oscillatory components, with guaranteed positive and smoothly varying instantaneous frequencies. Analysis on synthetic and real data demonstrates that this method promises higher spectral-spatial resolution than ...

This paper presents a new approach for human cataract automatical detection based on ultrasound signal processing. Two signal decomposition techniques, empirical mode decomposition and discrete wavelet transform are used in the presented method. Performance comparison of these two decomposition methods when applied to this specific ultrasound signal is given. Described method includes ultrasoni...