This paper introduces a new instantaneous frequency computation approach -Counting Instantaneous Frequency for a general class of signals called simple waves. The classsimple wave contains a wide range of continuous signals for which the concept instantaneous frequency has a perfect physical sense. The concept of -Counting Instantaneous Frequency also applies to all the discrete data. For all t...

Blind voice separation refers to retrieve a set of independent sources combined by an unknown destructive system. The proposed separation procedure is based on processing of the observed sources without having any information about the combinational model or statistics of the source signals. Also, the number of combined sources is usually predefined and it is difficult to estimate based on the ...

Abstract In view of the nonlinear characteristics of chaotic signal, a threshold denoising method of noisy chaotic signal based on empirical mode decomposition (EMD) is presented. Firstly, noisy chaotic signal is decomposed into several intrinsic mode function (IMF) by empirical mode decomposition. Secondly, the intrinsic mode functions of high frequency are respectively processed using thresho...

Empirical Mode Decomposition (EMD), introduced by Huang et al, in 1998 is a new and effective tool to analyze non-linear and non-stationary signals. With this method, a complicated and multiscale signal can be adaptively decomposed into a sum of finite number of zero mean oscillating components called as Intrinsic Mode Functions (IMF) whose instantaneous frequency computed by the analytic signa...

Previous work on Empirical Mode Decomposition in two dimensions typically generates a residue with many extrema points. In this paper we propose an improved method to decompose an image into a number of Intrinsic Mode Functions and a residue image with a minimum number of extrema points. We further propose a method for the variable sampling of the two-dimensional Empirical Mode Decomposition. S...

The concept of empirical mode decomposition (EMD) and the Hilbert spectrum (HS) has been developed rapidly in many disciplines of science and engineering since Huang et al. (1998) invented EMD. The key feature of EMD is to decompose a signal into so-called intrinsic mode function (IMF). Furthermore, the Hilbert spectral analysis of intrinsic mode functions provides frequency information evolvin...

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...