It is proposed to use time-frequency analysis of vocal fold's onset signal for diagnosis of different phonation disorders evoked by pathological changes. The vibration signals are acquired by direct optical inspection of the glottis using an endoscope and a high speed CCD camera system. Because of their outstanding performance the Wigner distribution is used as an analysis tool. It is shown tha...

The Fourier transform usually has been used in the past for analysis of stationary and periodic signals. Its interest is the knowledge of spectral components existing in a waveform; it doesn't matter the moment where they happen. However, when the time localization of the spectral components is needed, the Wavelet Transform (WT) can be used to obtain the optimal timefrequency representation of ...

The problem of overlapping harmonics is particularly acute in musical sound separation and has not been addressed adequately. We propose a monaural system based on binary time-frequency masking with an emphasis on robust decisions in timefrequency regions, where harmonics from different sources overlap. Our computational auditory scene analysis system exploits the observation that sounds from t...

A novel method for automatic ship detection based on the Wavelet Transform (WT) has been recently presented. The results obtained point out the potential of the use of a multiresolution time-frequency framework for the analysis of SAR imagery. On the one hand, this paper aims at reviewing the algorithm for automatic spot detection on speckled images. On the other hand, a novel algorithm for the...

In this paper, we propose two versions of a correlation-based blind source separation (BSS) method. Whereas its basic version operates in the time domain, its extended form is based on the timefrequency (TF) representations of the observed signals and thus applies to much more general conditions. The latter approach consists in identifying the columns of the (permuted scaled) mixing matrix in T...

We consider a two-dimensional demodulation framework for spectro-temporal analysis of the speech signal. We construct narrowband (NB) speech spectrograms, and demodulate them using the Riesz transform, which is a two-dimensional extension of the Hilbert transform. The demodulation results in timefrequency envelope (amplitude modulation or AM) and timefrequency carrier (frequency modulation or F...

In wireless networks, interferences between transmissions are modelled either in time or frequency domain. In this article, we jointly analyze interferences in the timefrequency domain using a stochastic geometry model assuming the total time-frequency resources to be a two-dimensional plane and transmissions from Internet of Things (IoT) devices timefrequency patterns on this plane. To evaluat...

In this paper, we consider the analysis of polynomial FM signals corrupted by additive heavy-tailed noise. Standard timefrequency techniques fail to analyze such signals. For that, we propose here a new technique, named the robust polynomial WignerVille distribution (r-PWVD) to handle this case. We show that this representation outperforms the robust Wigner-Ville distribution (rWVD) and the rob...

– Slow fluctuating radar targets have shown to be very difficult to classify using neural networks. This paper deals with the application of time-frequency decompositions for improving the performance of neural networks for this kind of targets. Several aspects, such as dimensionality reduction of the timefrequency representations and the optimum value of SNR for training are discussed. The pro...

This paper presents a comparative study of different wavelet denoising techniques and the results obtained were examined. The denoising process rejects noise by thresholding in the wavelet domain. It is observed that „rigrsure„ method gives optimum performance. Discrete wavelet transform has the benefit of giving a joint timefrequency representation of the signal. Also it is suitable for both s...