introduction breast cancer is one of the most common types of cancer among women.  early detection of breast cancer is the key to reducing the associated mortality rate. the presence of microcalcifications clusters (mccs) is one of the earliest signs of breast cancer. due to poor imaging contrast of mammograms and noise contamination, radiologists may overlook some diagnostic signs, specially t...

identification of damping parameter is usually more complicated and unreliable comparing to mass or stiffness identification in structural dynamics. there are many factors such as intermolecular friction, coulomb friction and viscous damping affecting the damping mechanisms in a structure. therefore it is difficult, and in some cases impossible, to describe the details of damping mechanisms by ...

There are many ways for detecting defects and classification and these methods have been applied to many areas of industry such as fabric or steel or etc. This paper proposes a method to classify defects of steel Bar In Coil (BIC) which has cylindrical shape. The wavelet transform has been used to detect or classify defects of images recently and the proposed classification algorithm uses wavel...

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...