Add to ORKGThe paper concentrates on the consequences of signal de-pendent spectral transformation from nite sets of arbi-trarily distributed samples. The spectrum support func-tion that reects the true nature of the signal spectral char-acteristics is discussed. The formation of transformation functions is based on a minimum variance lter approach. The simulation results demonstrate the capabilities of sig-nal dependent transformation for the analysis of stationary and non-stationary signals. The proposed method is par-ticularly applicable to cases where the signal is sampled non-uniformly with a density less than the Nyquist rate. 1
International audienceRecently, sub-Nyquist sampling of wideband signals has gained much attention i...
In nonuniform sampling (NUS), signal amplitudes and time stamps are delivered in pairs. Several meth...
The classical methods of evaluating the energy spectra of discretized deterministic and stochastic p...
This work is a part of a drastic revolution in the classical signal processing chain required in mob...
International audienceAn approach to the spectral estimation for some classes of non-stationary rand...
This work is a part of a drastic revolution in the classical signal processing chain required in mob...
Interpolation and spectral analysis of signals from finite number of samples is considered. When the...
Signal acquisition, signal reconstruction and analysis of spectrum of the signal are the three most ...
The paper describes the processing of non-stationary signals, which takes the advantages offered by ...
The paper addresses the problem of signal-dependent sampling of analogue signals according to local ...
The properties of the Gabor and Morlet transforms are examined with respect to the Fourier analysis ...
The discrete Fourier transform is extensively applied in spectrum analysis. However, the sampled sig...
It is shown that a number of equivalent choices for the calculation of the spectrum of a sampled sig...
It has been shown that the chosen numerical integration method corresponds to a realistic view of da...
Spectral analysis is a common part of the signal theory dealing with possibilities of representation...
International audienceRecently, sub-Nyquist sampling of wideband signals has gained much attention i...
In nonuniform sampling (NUS), signal amplitudes and time stamps are delivered in pairs. Several meth...
The classical methods of evaluating the energy spectra of discretized deterministic and stochastic p...
This work is a part of a drastic revolution in the classical signal processing chain required in mob...
International audienceAn approach to the spectral estimation for some classes of non-stationary rand...
This work is a part of a drastic revolution in the classical signal processing chain required in mob...
Interpolation and spectral analysis of signals from finite number of samples is considered. When the...
Signal acquisition, signal reconstruction and analysis of spectrum of the signal are the three most ...
The paper describes the processing of non-stationary signals, which takes the advantages offered by ...
The paper addresses the problem of signal-dependent sampling of analogue signals according to local ...
The properties of the Gabor and Morlet transforms are examined with respect to the Fourier analysis ...
The discrete Fourier transform is extensively applied in spectrum analysis. However, the sampled sig...
It is shown that a number of equivalent choices for the calculation of the spectrum of a sampled sig...
It has been shown that the chosen numerical integration method corresponds to a realistic view of da...
Spectral analysis is a common part of the signal theory dealing with possibilities of representation...
International audienceRecently, sub-Nyquist sampling of wideband signals has gained much attention i...
In nonuniform sampling (NUS), signal amplitudes and time stamps are delivered in pairs. Several meth...
The classical methods of evaluating the energy spectra of discretized deterministic and stochastic p...