Half-band filters are a class of important filters among digital filters, and have been widely used in many applications such as filter banks and wavelets. The conventional methods are mainly concerned with FIR half-band filters with exactly linear phase. However, the exactly linear phase filters have a drawback of large group delay when high-order filters are required. In this paper, the desig...

Compactly supported orthogonal wavelets are built on the Cantor dyadic group (the dyadic or a-series local field). Necessary and sufficient conditions are given on a trigonometric polynomial scaling filter for a multiresolution analysis to result. A Lipschitz regularity condition is defined and an unconditional P-convergence result is given for regular wavelet expansions (p > 1). Wavelets are g...

We propose a generalization of the Cohen-Daubechies-Feauveau (CDF) and 9/7 biorthogonal wavelet families. This is done within the framework of non-stationary multiresolution analysis, which involves a sequence of embedded approximation spaces generated by scaling functions that are not necessarily dilates of one another. We consider a dual pair of such multiresolutions, where the scaling functi...

we show how daubechies wavelets are used to solve kuramoto-sivashinsky type equations with periodic boundary condition‎. ‎wavelet bases are used for numerical solution of the kuramoto-sivashinsky type equations by galerkin method‎. ‎the numerical results in comparison with the exact solution prove the efficiency and accuracy of our method‎.

The rapid development of technology led to the need keep pace with it, especially in field image processing, because its importance get better results. In this paper, new discrete Chebyshev wavelet transforms (DChWT) derived from polynomials (ChP) were proposed and characterized. terms orthogonality approximation (convergence) mathematics, qualified transform into wavelets called (DChWT), depen...

Wavelet-based analysis versus Gaussian smoothing in statistical parametric mapping (SPM) for detecting and analyzing brain activity from functional magnetic resonance imaging (fMRI) data is presented. Detection of activation in fMRI data can be performed in the wavelet domain by a coefficient-wise statistical t-test. The link between the wavelet analysis and SPM is based on two observations: (i...

Wavelet networks (WNs) were introduced in 1992 as a combination of artificial neural radial basis function (RBF) networks and wavelet decomposition. Since then, however, WNs have received only a little attention. We believe that the potential of WNs has been generally underestimated. WNs have the advantage that the wavelet coefficients are directly related to the image data through the wavelet ...

IMAGE COMPRESSION Jan E. Odegard C. Sidney Burrus Department of Electrical and Computer Engineering Rice University, Houston, Texas 77005-1892, USA [email protected], [email protected] http: www-dsp.rice.edu ABSTRACT In this paper we introduce a new family of smooth, symmetric biorthogonal wavelet basis. The new wavelets are a generalization of the Cohen, Daubechies and Feauveau (CDF) biorthogonal wa...

Over the last number of years many different libraries of biorthogonal wavelets have been designed. In addition, the lifting scheme has been developed which unifies the design of biorthogonal wavelets using a simple approach. The lifting scheme allows the custom design of wavelets while maintaining the biorthogonal constraint on the filter bank. A drawback of the lifting scheme is that it does ...

This paper presents a new method for designing orthonormal wavelet filter banks using the Remez exchange algorithm. It is well known that orthonormal wavelet bases can be generated by paraunitary filter banks. Thus, synthesis of orthonormal wavelet bases can be reduced to the design of paraunitary filter banks. From the orthonormality and regularity of wavelets, we derive some conditions that m...