The induction motors effort to widely industrial fields. On the contrary, faults of the induction motors cause another faults of the whole system, because the faults of the induction motors often progress through long time. It is very important that diagnosis for diagnosis fault and extracted fault feature from the acquired signal using wavelet transform. Extracted features use the fault diagno...

Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required. Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the rail track...

The idea of using artificial neural network has proved useful for hyperspectral image classification. However, the high dimensionality of hyperspectral images usually leads to the failure of constructing an effective neural network classifier. To improve the performance of neural network classifier, wavelet-based feature extraction algorithms are applied to extract useful features for hyperspec...

An Approach Based On Wavelet Decomposition and Neural Network for ECG Noise

‘Steganography is a art, which enforcing for obscur one part of data or information within another’. this paper shown an image steganography scheme which based on neural network fusion in wavelet transform domain. The cover and stego image is dividing in its frequency coefficients components by wavelet transform domain, and neural network used as classifier. This paper performed on the 256*256 ...

This paper outlines a Wavelet Transform (WT) based Artificial Neural Network (ANN) input data pre-processing scheme and presents the results of localized gear tooth defect recognition tests by employing this proposed methodology. The methodology consists of calculating Daubechies’ 20-order (DAUB-20) mean-square dilation WTs of the data, and then selecting predominant wavelet coefficients distri...

In this paper, we aim to achieve two specific objectives. The first one is to examine the applicability of wavelet neural network (WNN) technique in ore grade estimation, which is based on integration between wavelet theory and Artificial Neural Network (ANN). Different wavelets are applied as activation functions to estimate Cu grade of borehole data in the hypogene zone of porphyry ore deposi...

Introduction: SPECT is a diagnostic imaging technique the main disadvantage of which is the existence of Poisson noise. So far, different methods have been used by scientists to improve SPECT images. The Wavelet Transform is a new method for de-noising which is widely used for noise reduction and quality enhancement of images. The purpose of this paper is evaluation of noise reduction in SPECT ...