In order to improve the measurement accuracy, in the traditional measuring method based on, by avoiding wave speed influence on fault location of transmission line method, and compares it with the combination of wavelet transform. This article selects dBN wavelet and three B spline wavelet contrast, compared them with new methods, through the Xi'an City Power Supply Bureau of the actual fault d...

We propose a new method for simulating a Gaussian process, whose spectrum diverges at one or multiple frequencies in 0; 1 2 ] (not necessarily at zero). The method utilizes a generalization of the discrete wavelet transform, the discrete wavelet packet transform (DWPT), and only requires explicit knowledge of the spectral density function of the process { not its autocovariance sequence. An ort...

The aim of this study is to evaluate a machine-learning method in which symbolic representations of folk songs are segmented and classified into tune families with Haar-wavelet filtering. The method is compared with previously proposed Gestaltbased method. Melodies are represented as discrete symbolic pitch-time signals. We apply the continuous wavelet transform (CWT) with the Haar wavelet at s...

A wavelet multiscale iterative regularization method is proposed for the parameter estimation problems of partial differential equations. The wavelet analysis is introduced and a wavelet multiscale method is constructed based on the idea of hierarchical approximation. The inverse problem is decomposed into a sequence of inverse problems which rely on the scale variables and are solved approxima...

This paper presents a wavelet-based Gaussian method (WGM) for the peak intensity estimation of energy dispersive X-ray fluorescence (EDXRF). The relationship between the parameters of Gaussian curve and the wavelet coefficients of Gaussian peak point is firstly established based on the Mexican hat wavelet. It is found that the Gaussian parameters can be accurately calculated by any two wavelet ...

Two methods for the identification of coherent structures in fluid flows are studied for possible combination in a hybrid method providing deeper insight and greater efficiency. One method uses wavelet transforms to partition the field into coherent and incoherent portions using a thresholding of the wavelet coefficients. The other method is based on the stability analysis of trajectories throu...

This paper proposes a method for extracting sub-images from a huge reference image by using learnt lifting wavelet filters. Lifting wavelet filters are biorthogonal wavelet filters containing free parameters developed by Sweldens. Our method is to learn such free parameters using some training sub-images so as to vanish their high frequency components. The learnt wavelet filters have the featur...

This papers gives an overview of wavelet transforms application to signal denoising problem. Wavelets perform well for this application and have been used before with great success. To further improve the transform efficiency adaptivity is introduced to traditional wavelet transforms. The lifting framework as a method to construct wavelets facilitates the effort to develop efficient adaptation ...

Deblurring in the presence of noise is a hard problem, especially in ultrasonic and CT images. In this paper, we propose a new method of image deblurring in presence of noise, using symmetric Daubechies complex wavelet transform. The proposed method is based on shrinkage of multilevel Daubechies complex wavelet coefficients, and is adaptive as it uses shrinkage function based on the variance of...