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Vibration signal plays very important role in fault diagnosis of machine because it carries dynamic information of the machine. Signal processing is essentially needed to process and analyse signal but it is difficult to process and analyse the noisy signal. In many cases the noise signal is even stronger than the actual vibration signal, so it is important to have some mechanism in which noise elimination...
We describe a method for physiological signal denoising based on the variational mode decomposition (VMD), the discrete wavelet transform (DWT), and constrained least squares (CLS) optimization. First, the noisy signal is decomposed into a sum of variational mode functions (VMFs) by VMD. Next, the DWT thresholding technique is applied to each VMF for denoising. Then, a weighted sum of the denoised...
This paper compares three biomedical image denoising techniques based on the recently introduced variational mode decomposition (VMD), the empirical mode decomposition (EMD), and the well-known discrete wavelet transform (DWT). The work focuses on using the VMD lowest mode or the EMD residue for denoising images corrupted with Gaussian noise, as opposed to DWT decomposition with thresholding. The...
The data interpolation is an essential part of Bidimensional Empirical Mode Decomposition (BEMD) of an image. In the decomposition process, local maxima and minima of the image are extracted at each iteration and then interpolated to form the upper and lower envelopes, respectively. Because of the properties of radial basis function (RBF) interpolators, they are good candidates for use in BEMD. However,...
Partial discharge detection in power transformers is discussed using a new approach that exploit the broad band of the Rogowski coils and the potential of two signal processing tools: discrete wavelet transform and empirical mode decomposition. Detecting and analyzing incipient activities of partial discharge can provide useful information to diagnostics and prognostics about transformer insulation...
Electrocardiogram (ECG) signal is useful in diagnosing the heart condition. Good quality ECG is utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, The electrocardiogram (ECG) signal may mix various kinds of noises while gathering and recording. In this paper, we propose a new ECG enhancement method based on the recently developed empirical...
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