In this paper, after reviewing the main points of Haar wavelet transform and chaotic trigonometric maps, we introduce a new perspective of Haar wavelet transform. The essential idea of the paper is given linearity properties of the scaling function of the Haar wavelet. With regard to applications of Haar wavelet transform in image processing, we introduce chaotic trigonometric Haar wavelet tran...

In view of the existing seismic signal analysis model there are some problems is Analysis of the result is bad, the accuracy is not high. This paper puts forward an algorithm based on discrete wavelet and generalized the ICA model of seismic signal analysis. First for continuous Wavelet transform exists redundant of problem, on standard small wave transform algorithm of transform domain in the ...

the idea of this paper is designing an automatic fault detection system based on fuzzy logic, therefore two signals of pmsm in fault condition are analyzed for inter turn fault detection: current and torque. in this fault type there is some distortion in these signals, but it is not good enough to detecting with fuzzy logic solely, so with combination of wavelet transform and fcm a new method f...

In this paper the faults diagnosis of induction machines based on the discrete wavelet transform (DWT) is detailed. The wavelet decomposition is used to extract the information from a signal over a wide range of frequencies. This analysis is performed in both time and frequency domains. The Daubechies wavelet is selected for the analysis of the stator current. Wavelet components appear to be us...

This paper presents a method for prediction short-term power demand of a vehicular power system. The forecasting of power demand is presented using wavelet decomposition and artificial neural network, a hybrid model which absorbs some merits of wavelet transform and neural network. The power demand time series is first decomposed into a certain number of levels with discreet wavelet transform a...

A new simple and efficient dual tree analytic wavelet transform based on Discrete Cosine Harmonic Wavelet Transform DCHWT (ADCHWT) has been proposed and is applied for signal and image denoising. The analytic DCHWT has been realized by applying DCHWT to the original signal and its Hilbert transform. The shift invariance and the envelope extraction properties of the ADCHWT have been found to be ...

the goal of this research is to predict total stock market index of tehran stock exchange, using the compound method of arima and neural network in order for the active participations of finance market as well as macro decision makers to be able to predict trend of the market. first, the series of price index was decomposed by wavelet transform, then the smooth's series  predicted by using...

Wavelet denoising techniques are used to remove additive Gaussian noise by thresholding the wavelet coe cients. Like other transform based lters, wavelet shrinkage methods provide blur or visual artifacts that are exhibited in the neighborhood of image edges. The motive for implementing the Hybrid Wavelet Transform Filter (HWTF) is to provide discriminate smoothing operator for noise removal. T...

Wavelet analysis is a time – frequency analysis method, time-frequency localization problems are well solved, this paper analyzes the basic principles of the wavelet transform and the relationship between the signal singularity Lipschitz exponent and the local maxima of the wavelet transform coefficients mold, the principles of wavelet transform in image denoising are analyzed, the disadvantage...