The EEG signals are recorded between electrodes placed in standard positions on the scalp. They have a typical amplitude of 2-100 μV and a frequency spectrum from 0.1 ÷ 50 Hz. The potential at the scalp derives from electrical activity of large synchronized groups of neurons inside the brain. EEG activity in particular frequency bands is often correlated with particular cognitive states. There ...

The study of cetacean vocalizations is usually based on spectrogram analysis. The feature extraction is obtained from 2D methods like the edge detection algorithm. Difficulties appear when signal-to-noise ratios are weak or when more than one vocalization is simultaneously emitted. This is the case for acoustic observations in a natural environment and especially for the killer whales which swi...

BACKGROUND Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate betwee...

In this paper, empirical mode decomposition technique is used to analyze the spatial slip distribution of five past earthquakes. It is shown that the finite fault slip models exhibit five empirical modes of oscillation. The last intrinsic mode is positive and characterizes the non-stationary mean of the slip distribution. This helps in splitting the spatial variability of slip into trend and th...

This paper is devoted to the analysis of time series using the Empirical Mode Decomposition (EMD) method. This method decomposes the analyzed time series into a small set of narrow-band components (modes) that fully represent the original time series. The modified EMD method that eliminates excessive changes of individual mode periods is proposed and evaluated on one example application of indu...

In order to detect coal gangue interface on fully mechanized mining face, a new method of vibration signal analysis of coal and gangue based on Hilbert-Huang transform is presented in this paper. At first Empirical mode decomposition algorithm was used to decompose the original vibration signal of coal and gangue into intrinsic modes for further extract meaningful information contained in respo...

Empirical Mode Decomposition (EMD) is an emerging topic in signal processing research, applied in various practical fields due in particular to its data-driven filter bank properties. In this paper, a novel EMD approach called X-EMD (eXtended-EMD) is proposed, which allows for a straightforward decomposition of monoand multivariate signals without any change in the core of the algorithm. Qualit...