In this article the limited application of the non-stationary signals spectra classical analysis using the Fourier transform is substantiated. It is shown that Fourier transform has benefits at periodic signals analysis and limitations when non-stationary signals processing. Authors compared various time-frequency methods of analysis used at signals and circuits in dynamic state. The examples of Fourier window transform application are considered. The dynamic transmission coefficient method for second order circuits time-frequency parameters calculation is studied. The advantages of wavelet transforms application at non-stationary signals analysis are stated
International audienceThe authors present a practical guide for studying nonstationary data on human...
This paper serves the idea of applying joint time-frequency representations in electrical engineerin...
A traditional frequency analysis is not appropriate for observation of properties of non-stationary ...
Signals consisting of multiple frequencies and changing their amplitude while propagating in time ge...
The aim of the data analysis is to explore the main characteristics of the signal by a signal transf...
All electrical signals can be described either as a function of time or of frequency. When we observ...
Representation of signals in time and frequency domain has been of interest in signal processing are...
Wavelet transform is a term from signal analysis. It is mostly used in physics, but also in finance,...
S-transform is a new time-frequency analysis method, which is deduced from short-time Fourier transf...
This thesis discusses the characteristics of time-windows and their application in frequency analysi...
This bachelor thesis is dealing with explanation of time-frequency signal analysis. Basic definition...
Time analysis and frequency analysis are both well-established ways in engineering to gain more know...
In this paper, multiresolution signal processing is described, by the continuous Fourier transform, ...
Time-frequency analysis of signals or images deals with mathematical transforms of continuous or dis...
The Fourier Transform (FT) is the well-known classical representation of signals components by provi...
International audienceThe authors present a practical guide for studying nonstationary data on human...
This paper serves the idea of applying joint time-frequency representations in electrical engineerin...
A traditional frequency analysis is not appropriate for observation of properties of non-stationary ...
Signals consisting of multiple frequencies and changing their amplitude while propagating in time ge...
The aim of the data analysis is to explore the main characteristics of the signal by a signal transf...
All electrical signals can be described either as a function of time or of frequency. When we observ...
Representation of signals in time and frequency domain has been of interest in signal processing are...
Wavelet transform is a term from signal analysis. It is mostly used in physics, but also in finance,...
S-transform is a new time-frequency analysis method, which is deduced from short-time Fourier transf...
This thesis discusses the characteristics of time-windows and their application in frequency analysi...
This bachelor thesis is dealing with explanation of time-frequency signal analysis. Basic definition...
Time analysis and frequency analysis are both well-established ways in engineering to gain more know...
In this paper, multiresolution signal processing is described, by the continuous Fourier transform, ...
Time-frequency analysis of signals or images deals with mathematical transforms of continuous or dis...
The Fourier Transform (FT) is the well-known classical representation of signals components by provi...
International audienceThe authors present a practical guide for studying nonstationary data on human...
This paper serves the idea of applying joint time-frequency representations in electrical engineerin...
A traditional frequency analysis is not appropriate for observation of properties of non-stationary ...