EEG is widely used to record the electrical activity of the brain for detecting various kinds of diseases and disorders of the human brain. EEG signals are contaminated with several unwanted artifacts during EEG recording and these artifacts make the analysis of EEG signal difficult by hiding some valuable information. Time-frequency representation of electroencephalogram (EEG) signal provides ...

This paper presents the time domain and timefrequency domain analysis results of incipient events in single-phase distribution transformers. This analysis will aid in the development of an automatic detection method for internal incipient faults in the transformers. The detection method can provide information to predict failures ahead of time so that the necessary corrective actions are taken ...

This article presents the use of the synchrosqueezing transform (SST) for the timefrequency analysis of shock and vibration measurements. The time-frequency resolution properties of SST is demonstrated by analyzing acceleration measurements from pallets dropped from heights and vibration of pallets acquired in controlled laboratory settings. The article presents results that indicate that SST, ...

By use of window functions, time-frequency analysis tools like Short Time Fourier Transform overcome a shortcoming of the Fourier Transform and enable us to study the timefrequency characteristics of signals which exhibit transient oscillatory behavior. Since the resulting representations depend on the choice of the window functions, it is important to know how they influence the analyses. One ...

We prove the boundedness of a general class of Fourier multipliers, in particular of the Hilbert transform, on modulation spaces. In general, however, the Fourier multipliers in this class fail to be bounded on L spaces. The main tools are Gabor frames and methods from time-frequency analysis.

The wavelet transform is one of the most important method used in signal processing. In this study, we have introduced frequency-energy characteristics of local earthquakes using discrete wavelet transform. Frequency-energy characteristic was analyzed depend on difference between P and S wave arrival time and noise within records. We have found that local earthquakes have similar characteristic...

This paper proposes a fault-location method for voltage-source converter (VSC)-based high-voltage direct current (VSC-HVDC) systems. This method relies on the current frequency components generated by faults in the cable, and requires the arrival time of the frequency components at two terminals. The S transform is a time–frequency analysis tool that is superior to the wavelet transform in some...

Nonlinearities are often encountered in the analysis and processing of real-world signals. Most existing approaches to nonlinear signal processing characterize the nonlinearity in the time domain or frequency domain. In fact, there are good reasons for characterizing nonlinearity using more general signal representations like the wavelet expansion. Wavelet expansions often provide very concise ...

An image resolution enhancement technique based on interpolation of the high frequency subband images obtained by discrete wavelet transform (DWT) and the input image. The edges are enhanced by introducing an intermediate stage by using stationary wavelet transform (SWT). DWT is applied in order to decompose an input image into different subbands. Then the high frequency subbands as well as the...

The sinusoidal transform, as developed by Quatieri and McAulay, provides a sparse representation for speech signals by taking advantage of psychoacoustic masking. The currently reported work takes the sinusoidal transform one step further by considering the frequency resolution abilities of the human auditory system in more detail. The new transform is based on the wavelet principle of variable...