Tsung-Ying Sun, Member, IEEE, Chan-Cheng Liu, Sheng-Ta Hsieh, Tsung-Ying Tsai, and Jyun-Hong Jheng, Optimal Determination of Wavelet Threshold and Decomposition Level via Heuristic Learning for Noise Reduction, IEEE Conference on Soft Computing in Industrial Applications (SMCia/08), June 25-27...
Wavelet decomposition is a new approach to understanding and modelling turbulence, based on phase-space structures, allowing the determination of “local” spectra1. The overall objective of the proposed work is to develop a tool to identify “wavelet patterns” and their role in turbulence dynamics...
In this work, the noisy-S1 heart signal was investigated to separate M1 and T1 components of it by making the comprehensive analysis of the determination of wavelet function-level pair for the decomposition and reconstruction of artificial S1 by using multiresolution analysis (MRA) and discrete ...
To achieve this goal, a forward search algorithm is proposed for determination of an appropriate wavelet decomposition level. Two EEG databases from University of Bonn and University of Freiburg are used for illustration of applicability of the proposed method to both epilepsy diagnosis and epileptic ...
In this study, by optimization, wavelet packet function, decomposition level and number of hidden nodes for WPTLMBP method were selected as Db2, 2, and 4 respectively. A program PWPTLMBP was designed to perform simultaneous kinetic determination of Cu(II), Fe(III), and Ni(II). The ...
We perform tests using simulation data and design a filter using the optimum selected wavelet parameters (three-level decomposition, level-1 zeroed out, subband-dependent threshold, a soft-thresholding and spline-based discrete dyadic wavelet transform (DDWT)), which we call a modified wavelet ...
and the fit worsens. As shown in Fig.6(d), with a wavelet decomposition level of one, the data is segregated into only one low-frequency and one high-frequency component, yielding an inadequate fit. Increasing the number of wavelet decomposition levels reduces the prediction error and enhances...
The coefficients at scale 8 from the db2 decomposition are squared and the resulting time series is represented by an approximation of the 4'th level Discrete Wavelet Transform (DWT) using a Haar wavelet. A threshold detector is then applied to the resulting time series to determine the Lg ...
for the waveform and also as a quick indication of frequency content[98]. The frequency band for each level can be computed from the sampling frequency. Eachdecomposition leveldivides the band into two halves, with approximation being the lower half and detail being the upper half. ...
One-level wavelet decomposition is applied to grayscale image and the mean of the energy is calculated in a window on the wavelet coefficients. The size ofReferences (32) H.D. Cheng et al. Color image segmentation: advances and prospects Pattern Recognition (2001) A. Sengur Wavelet transform...