The jamor purpose of the present research is to predict the total stock market index of Tehran Stock Exchange, using a combined method of Wavelet transforms, Fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.To do so, first the prediction was made by neural network, then a series of price index was decomposed by w...

Wavelet transforms originated in geophysics in the early 1980s for the analysis of seismic signals. Since then, significant mathematical advances in wavelet theory have enabled a suite of applications in diverse fields. In geophysics the power of wavelets for analysis of nonstationary processes that contain multiscale features, detection of singularities, analysis of transient phenomena, fracta...

Spatial and/or temporal variabilities of clouds is of paramount importance for at least two intensely researched sub-problems in global and regional climate modeling: • cloud-radiation interaction where correlations can trigger three-dimensional (3D) radiative transfer effects; and • dynamical cloud modeling where the goal is to realistically reproduce the said correlations. We propose wavelets...

This paper presents a brief overview of the multiresolution transform designs used in a few image and video compression systems, namely H.264, PTC (progressive transform coder), and JPEG2000. The first two use hierarchical transforms, and the third uses wavelet transforms. We review the basis constructions for the hierarchical transforms, and compare some of their characteristics with those of ...

One of the most remarkable properties of the continuous curvelet and shearlet transforms is their sensitivity to the directional regularity of functions and distributions. As a consequence of this property, these transforms can be used to characterize the geometry of edge singularities of functions and distributions by their asymptotic decay at fine scales. This ability is a major extension of ...