Biorthogonal wavelets are essential tools for numerous practical applications. It is very important that wavelet transforms work numerically stable in floating point arithmetic. This paper presents new results on the worst-case analysis of roundoff errors occurring in floating point computation of periodic biorthogonal wavelet transforms, i.e. multilevel wavelet decompositions and reconstructio...

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...

ABSTRACT: Wavelet transforms have become one of the most important and powerful tool of signal representation. Nowadays, it has been used in image processing, data compression, and signal processing. Here, we are discussing about the basic concept for Wavelet Transforms and the fast algorithm of Wavelet Transform. Now-a-days the wavelet theorems make up very popular methods of image processing,...

We analyze quasiasymptotic boundedness of distributions and their wavelet transforms, in general, as well as for a class of α− exponentially bounded distributions and their wavelet transforms in particular. The main idea of this paper is to use, instead of the quasiasymptotic behaviour, the notion of quasiasymptotic boundedness. In this way we obtain new Abelian type theorems for the wavelet tr...

Roger L. Claypoole, Jr. and Richard G. Baraniuk, Rice University Summary We introduce and discuss biorthogonal wavelet transforms using the lifting construction. The lifting construction exploits a spatial{domain, prediction{error interpretation of the wavelet transform and provides a powerful framework for designing customized transforms. We discuss the application of lifting to adaptive and n...

This paper takes up the design of wavelet tight frames that are analogous to Daubechies orthonormal wavelets | that is, the design of minimal length wavelet lters satisfying certain polynomial properties, but now in the oversampled case. The oversampled dyadic DWT considered in this paper is based on a single scaling function and two distinct wavelets. Having more wavelets than necessary gives ...

The undecimated discrete wavelet transform (UDWT) is a powerful image denoising tool, well-known to perform better than orthogonal wavelets. Unlike the case of orthogonal wavelets, noise as well as signal in the UDWT domain are non-white. Because of this inter-pixel correlation, scalar operations such as thresholding do not take full advantage of the power of UDWT. In this paper, we present a m...

We investigate the formulation of boundary compensated wavelet transforms supported on a nite interval. A uni ed approach to boundary compensated wavelet transforms is presented which fosters new insights into previous constructions, including both continuous and discrete approaches to the problem. The framework enables the design of boundary-compensated transforms with speci c properties, incl...

Wavelet domain denoising has recently attracted much attention , mostly in conjunction with the coeecient-wise wavelet shrinkage proposed by Donoho 1]. While shrinkage is asymp-totically minimax-optimal, in many image processing applications a mean-squares solution is preferable. Most MMSE solutions that have appeared so far are based on an un-correlated signal model in the wavelet domain, resu...

In geophysical exploration different types of measurements are used to probe the same subsurface region. In this paper we show that the wavelet transform can aid the process of linking different data types. The continuous wavelet transform, and in particular the analysis of amplitudes along wavelet transform modulus maxima lines, is a powerful tool to analyze the characteristic properties of lo...