We present a new method for separation of the rhythms of the electroencephalogram (EEG) signal. The proposed method is based on the Hilbert-Huang transform (HHT). The HHT consists two steps namely empirical mode decomposition (EMD) and the Hilbert transform (HT). The EMD decomposes EEG signal into set of narrow-band intrinsic mode functions (IMFs), and the Hilbert transformation of these IMFs p...

A new method for analysing nonlinear and non-stationary data has recently been developed, namely the partial-differential-equation (PDE) transform. The PDE transform is based on the use of coupled arbitrarily high order PDEs to decompose signals and images into various functional frequency modes, which allow perfect reconstruction of the original signals and images. The PDE transform is compare...

There are some methods to decompose a signal into different components such as: Fourier decomposition and wavelet decomposition. But they have limitations in some aspects. Recently, there is a new signal decomposition algorithm called the Empirical Mode Decomposition (EMD) Algorithm which provides a powerful tool for adaptive multiscale analysis of nonstationary signals. Recent works have demon...

Abstract: In this paper we consider time scale synchronization between two different timedelay systems. Due to existence of intrinsic multiple characteristic time scales in the chaotic time series, the usual definition for the calculation of phase failed. To define the phase, we have used empirical mode decomposition and the results are compared with those from continuous wavelet transform. We ...

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...

Empirical mode decomposition (EMD) and Empirical wavelet transform (EWT) are recently developed adaptive signal processing tools. These techniques decompose a signal accordingly to its contained information. The main issue with EMD is its lack of theory and in case of EWT a prior knowledge of the signal is required. IMF’s obtained as a result of applying EMD are quasi-orthogonal .This paper sug...

Ground moving target indication (GMTI) in foliage environment is a challenging problem, because the strong echoes from dense foliage environment and big attenuation of the radar microwave often make it difficult for traditional time frequency distributions to clearly and locally represent the Doppler frequency. This paper introduced a new approach to improve the performance of GMTI. This so-cal...

In order to design and implement a wave compensation system to reduce the relative motion between two side-by-side ships in waves, a new method to process measured data of ship model test with contact measurement to study the characteristics of relative motion was presented. The reference coordinate systems and relative motions were defined, and the scheme of the model test was described. Then ...

Modal parameters of power transformer winding are closely related to transformer manufacturing and detection technology of winding deformation based on vibration analysis method. Aimed at identifying the modal parameters of transformer winding accurately, a modal experiment is designed and made on a real 10 kV power transformer. An improved Empirical Mode Decomposition (EMD) algorithm is propos...

The Long-Term Pavement Performance (LTPP) database contains surface profile data for numerous pavements that are used mainly for computing International Roughness Index (IRI).(2) In order to obtain more information from these surface profiles, a Hilbert-Huang Transform (HHT) based surface profile algorithm was developed to analyze LTPP field road profile data in order to extract smoothed, consi...