1. introduction in recent years, regarding climate changes, the analysis of natural variability of climate at different time scales has attracted a lot of attention. while, the data series with short statistical period just shows a likelihood estimation of a few decades of climate variability, the data series with long period shows the fluctuations of several decades with statistical importance...

Chirps are signals (or sums of signals) that may be characterized by a local (i.e. time-dependent) amplitude and a local frequency. Time-frequency representations such as wavelet representations are well adapted to the characterization problem of such chirps. Ridges in the modulus of the transform determine regions in the transform domain with a high concentration of energy, and are regarded as...

In this paper a method is presented that parameterizes orthogonal wavelet transforms with respect to their properties (i.e. compact support, vanishing moments, regularity , symmetry) and also takes into considerations a simple implementation of the transform. The parameter space is given by the rotation angles of the orthogonal 2 2 rotations used in the lattice lters that realize the diierent s...

This paper reviews two different uses of the continuous wavelet transform for modal identification purposes. The properties of the wavelet transform, mainly energetic, allow to emphasize or filter the main information within measured signals and thus facilitate the modal parameter identification especially when mechanical systems exhibit modal coupling and/or relatively strong damping.

In this paper we apply the wavelets methodology to the analysis of the comovements of for some MENA countries from June 1997 until March 2005. We decompose weekly stock market returns into di¤erent time scale components using the non-decimated discrete wavelet transform and then analyze the relationships among these variables at the di¤erent time scales. Keywords : Stock market returns, Wavelet...

Abstract. In order to get an efficient representation of images which contain orientated edges we construct a directional wavelet basis for L(R). The wavelets basis consists of Haar wavelets with compact support on triangles. In comparison with the classical wavelet transform our functions offer two more directions (diagonal directions). Applying our simple wavelet system to image denoising and...