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The detection of partial discharge (PD) signals has proven extremely important to diagnose the integrity of the insulation in high voltage equipments. The measurements of such signals are often accompanied by noise from different sources, which can compromise the data analysis. Numerous wavelet shrinkage denoising techniques have been discussed recently in the literature. This article proposes an...
Partial Discharge (PD) measurement is widely adopted for assessing the insulation conditions of high voltage (HV) equipment. Wavelet transformation (WT) is one the de-noising techniques to extract PD signals from a variety of environmental noises and interferences. In wavelet-based PD signal de-noising, mother wavelet selection is one of the major challenges. This paper proposes a novel level-based...
Wavelets are designed to comprise certain properties that would make them a useful mathematical tool for signal processing. One application of discrete wavelet transform (DWT) is in analyzing financial time series data. The purpose of this paper is to apply DWT and stationary (discrete) wavelet transform (SWT), namely Haar, Daubechies, Symmlet and Coiflet in denoising a financial time series data...
In this paper, a novel image denosing scheme is proposed by applying 2D dual-tree complex wavelet transform (DTCWT) to the second bandelet transform. Compared with traditional discrete wavelet transform (DWT), the DTCWT has nearly shift invariant and directionally selective in two and higher dimensions important properties, which are suitable for image denoising. The bandelet transform has offer an...
The finite Ridgelet transform (FRIT) was widely used as a sparse representation for images that with linear singularities. Unfortunately, the ldquowrap aroundrdquo effect restricts its application in image compression and denoising. In this paper, The MAP estimator is applied to the coefficients in the finite Radon transform (FRAT) in order to select the fitted FRAT columns for 1-DCT and 1-DWT. Furthermore,...
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