The prediction of epileptic seizures is a very attractive issue for all patients suffering from epilepsy in EEG (electroencephalograph) signals. It can assist to develop an intervention system to control / prevent upcoming seizures and change the current treatment method of epilepsy. This paper describes a new method based on wavelet transform and fuzzy similarity measurement to predict the sei...

Analysis of tides and internal waves from model studies in the South China Sea is done using three techniques. We summarize results from standard Fourier methods, continuous wavelet analysis and the direct scattering transform. Because the Fourier and wavelet analysis are inherently linear methods their utility in application to nonlinear dynamics is often questioned. Nevertheless, they have sh...

In this correspondence, a novel wavelet-based approach to recover continuous-tone (contone) images from halftone images is presented. Wavelet decomposition of the halftone image facilitates a series of spatial and frequency selective processing to preserve most of the original image contents while eliminating the halftone noise. Furthermore, optional nonlinear filtering can be applied as a post...

We present an application of wavelet-based Information Theory quantifiers (Normalized Total Shannon Entropy, MPR-Statistical Complexity and Entropy-Complexity plane) on red blood cells membrane viscoelasticity characterization. These quantifiers exhibit important localization advantages provided by the Wavelet Theory. The present approach produces a clear characterization of this dynamical syst...

Long term memory has frequently been observed in physical time series. Statistical theory for long term memory stochastic processes is radically different from the standard time series analysis, which assumes short term memory. The Allen variance is a particular measure of variability developed for long term memory processes. This variance can be interpreted as a Haar wavelet coefficient varian...

We perform a multiscale analysis of the backscattering properties of a complex interface between water and a layer of randomly arranged glass beads with diameter D=1 mm. An acoustical experiment is done to record the wavelet response of the interface in a large frequency range from lambda/D=0.3 to lambda/D=15. The wavelet response is a physical analog of the mathematical wavelet transform which...

This thesis deals with applied mathematics with wavelets as a joint subject. There is an introduction and two extensive papers, of which one is already published in an international journal. The introduction presents wavelet theory including both the discrete and continuous wavelet transforms, the corresponding Fourier transforms, wavelet packets and the uncertainty principle. Moreover, it is a...

A lot of material has been written about wavelet theory. Most of these texts provide an elegant framework from the functional and real analysis point of view. The complete infinite dimensional space (the set of all functions such that ) is generally used to develop the theory, but this cannot be directly applied to computer software, because the concept of a non denumerable infinite set of vect...

Wavelet theory has a profound impact on signal processing as it offers a rigorous mathematical framework to the treatment of multiresolution problems. The combination of soft computing and wavelet theory has led to a number of new techniques. On the other hand, as a new generation of learning algorithms, support vector regression (SVR) was developed by Vapnik et al. recently, in which ε-insensi...