Automation of power system fault identification using information conveyed by the wavelet analysis of power system transients is proposed. Probabilistic Neural Network (PNN) for detecting the type of fault is used. The work presented in this paper is focused on identification of simple power system faults. Wavelet Transform (WT) of the transient disturbance caused as a result of occurrence of f...

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...

a r t i c l e i n f o a b s t r a c t Keywords: Reverse Monte Carlo EXAFS Wavelet analysis Germanium Rhenium trioxide In this work we present the Reverse Monte Carlo (RMC) modeling scheme, designed to probe the local structural and thermal disorder in crystalline materials by fitting the wavelet transform (WT) of the EXAFS signal. Application of the method to the analysis of the Ge K-edge and R...

In this paper, a prototype wavelet and probabilistic based neural network classifier for recognizing rotor bar defects is implemented and tested under various transient signals. The wavelet transform (WT) technique is integrated with the neural network model to extract rotor fault features. Firstly, the multiresolution analysis technique of WT and the particle swarm optimization (PSO) theorem a...

Detecting stratigraphic discontinuities using well log data is a fundamental task in petroleum geosciences projects. Wavelet transforms (WT) and S-transform (ST) of well log data can provide objective identification of lithological interfaces to aid in this effort. The continuous wavelet transform (CWT) of a time series gives the wavelet correlation coefficients (i.e. similarity) between the gi...

In this paper, an analog implementation of the Wavelet Transform (WT) is presented. The circuit is based on the Dynamic Translinear (DTL) circuit technique and implements, by means of cascade connected complex first order systems, an analog filter whose impulse response is a Gabor function, a function most widely used for frequency analysis among wavelet functions. From simulations, it is demon...

In MPEG-2 HDTV, the bandwidth and size of memory requirements are very large. These requirements increase system design difficulty and the hardware cost is high. There are a lot of compression algorithms that can reduce the size of the memory, but the algorithms are too complex. Here, we propose a simple algorithm to provide low complexity hardware and high quality video. Our algorithm is based...

Electroencephalography (EEG) is widely used in clinical settings to investigate neuropathology. Since EEG signals contain a wealth of information about brain functions, there are many approaches to analyzing EEG signals with spectral techniques. In this study, the short-time Fourier transform (STFT) and wavelet transform (WT) were applied to EEG signals obtained from a normal child and from a c...

Magnetic resonance (MR) images are normally corrupted by random noise which makes the automatic feature extraction and analysis of clinical data complicated. Hence there is a necessity to denoise MR images for better analysis. Therefore, several denoising methods have been applied to improve MR image quality. Disadvantage of previous methods are reconstruction process is complicated and time co...

Image coding requires a small bit rate for high-speed data transmission and a small space for data storage. Simultaneously, the peak signal to noise ratio (PSNR) has to be maintained. In this paper, first algorithm we present a method of image coding design using wavelet transform (WT). By applying the WT for defining groups of pixels with the same intensity in spatial domain, the groups of pix...