a r t i c l e i n f o a b s t r a c t Keywords: Time–frequency analysis Windowed Fourier transform Wavelet transform Synchrosqueezing Time–frequency representations (TFRs) of signals, such as the windowed Fourier transform (WFT), wavelet transform (WT) and their synchrosqueezed versions (SWFT, SWT), provide powerful analysis tools. Here we present a thorough review of these TFRs, summarizing al...

Uninterruptible power supply is the main motive of power utility companies that motivate them for identifying and locating the different types of faults as quickly as possible to protect the power system prevent complete power black outs using intelligent techniques. Thus, the present research work presents a novel method for detection of fault disturbances based on Wavelet Transform (WT) and I...

As it is known, the basis of the modern analytical chemistry is the instrumental analysis methods based on the evaluation of analytical signals such as spectra, chromatograms, kinetic curves and others obtained from instruments. Nowadays, the traditional evaluation of analytical signals may not always provide the desired results for the chemical and pharmaceutical analysis, where most of the an...

A network of spinal neurons known as central pattern generator (CPG) produces the rhythmic motor patterns required for coordinated swimming, walking, and running in mammals. Because the output of this network varies with time, its analysis cannot be performed by statistical methods that assume data stationarity. The present work uses short-time Fourier (STFT) and wavelet-transform (WT) algorith...

Continuous and Discrete Wavelet Transform (WT) are used to create text-dependent robust to noise speaker recognition system. In this paper we investigate the accuracy of identification the speaker identity in nonstationary signals. Three methods are used to extract the essential speaker features based on Continuous, Discrete Wavelet Transform and Power Spectrum Density (PSD). To have better ide...

This paper presents an algorithm to detect and classify voltage sag causes based on Wavelet Transform (WT) and Probabilistic Neural Network (PNN). A technique is required which is capable of extracting both time-frequency information to identify the causes which contribute to power quality disturbances. Wavelet transform based on multiresolution analysis is used to extract the features from the...

The wavelet multiscale edge representation of signals developed by Mallat and Zhong provides a new tool for signal and image processing. We built up a tree structure of wavelet-transform(WT) maxima and developed metrics for analyzing the WT maxima tree. These metrics fall into two classes corresponding to two perceptual criteria, scaling and spatial stabilities, for discriminating features from...

This paper describes a signal processing algorithm that utilizes wavelet transform and autoregressive modeling to identify heart sounds and to generate clinical features that characterize systolic and diastolic heart murmurs. A wavelet transform (WT) based on the Daubechies wavelet was adopted to facilitate the identification of the first and second heart sounds (S1 and S2) and to isolate systo...

On-line vibration monitoring of Rotary Machines is a fundamental axis of development and industrial research. Its purpose is to provide knowledge about the working condition of machines at each moment without stopping the production line. This method allows avoiding the production losses related to breakdowns and reducing overall maintenance costs. Bearing fault diagnosis is important in vibrat...