In this paper, a new efficient feature extraction method based on the adaptive threshold of wavelet package coefficients is presented. This paper especially deals with the assessment of autonomic nervous system using the background variation of the signal Heart Rate Variability HRV extracted from the wavelet package coefficients. The application of a wavelet package transform allows us to obtai...

The main task in wavelet analysis (decomposition and reconstruction) is to find a good wavelet function (mother wavelet) to perform an optimal decomposition. The goal of most wavelet researches is to create a set of basis functions and transforms that will give an informative, efficient and useful description of a signal. It is better if the wavelet function is adapted to the signal, because th...

Biometric recognition systems use measures from the body itself to determine the identity of an individual. The electrocardiogram (ECG) has been increasingly used as a biometric measure for person identification, as it is an easily measurable characteristic of all individuals. Our method for ECG acquisition follows an off-the-person approach, using a single ECG lead with non-gelled electrodes p...

In the present paper, Wavelet Networks, are proven to be, as well as many other neural paradigms, a speci c case of the generic paradigm named Weighted Radial Basis Functions Networks. Moreover, a fair comparison between Wavelet and more traditional WRBF networks for function approximation is attempted, in order to demonstrate that the performance depends only on how good the chosen mother/acti...

Photoplethysmography is a simple way for heart rate detection. However due to low level of detected signal, easily prone to motion artifacts and noise. In this paper DWT method is used to reduce the effect of noise, thereby calculate the heart rate. A comparative study of detecting heart rate using different mother wavelet is also discussed. Keywords— Heart beats, ECG, Photoplethysmography, Pea...

This paper presents a new wavelet-network-based technique for 1D and 2D functions’ approximation. Classical training algorithms start with a predetermined network structure which can be either insufficient or overcomplicated. Furthermore, the resolutions of wavelet networks training problems by gradient are characterized by their noticed inability to escape of local optima. The main feature of ...

The fetal electrocardiogram (fECG) monitoring yields important information about the fetus condition during pregnancy and it consists in collecting electrical signals by some sensors on the body of the mother. The Independent Component Analysis (ICA) has been widely exploited to isolate the fECG, while wavelet transform has been used as post-processing tool. Here we propose to fit the recently ...

This paper proposed an improved algorithm applied in video intelligent traffic control system for vehicle detection. The accuracy of original algorithm, which is based on the comparision of contrast and luminance distortion of present image with background, reduces greatly under bad weather because of false detection caused by noises in captured images. In this paper we chose Daubechies wavelet...

The admissibility condition of a mother wavelet is explored in the context of quantum optics theory. By virtue of Dirac’s representation theory and the coherent state’ property we derive a general formula for finding Mexican hat wavelets.

In this paper, we develop the theory of the wavelet transform over Galois elds. To avoid the limitations inherent in the number theoretic Fourier transform over nite elds, our wavelet transform relies on a basis decomposition in the time domain rather than in the frequency domain. First, we characterize the in nite dimensional vector spaces for which an orthonormal basis expansion of any sequen...