This paper describes an approach for texture characterization based on various wavelet decomposition transforms and its application for the discrimination of visually similar renal stone images. The proposed feature extraction algorithm applies Daubechies, Symlet, Coieflet, orthogonal and reverse biorthogonal wavelet transforms and uses approximation and detail coefficients to characterize rena...

As shown by Dahmen, Harbrecht and Schneider [7, 23, 32], the fully discrete wavelet Galerkin scheme for boundary integral equations scales linearly with the number of unknowns without compromising the accuracy of the underlying Galerkin scheme. The supposition is a wavelet basis with a sufficiently large number of vanishing moments. In this paper we present several constructions of appropriate ...

Finding a good wavelet for a particular application and type of input data is a difficult problem. Traditional methods of wavelet design focus on abstract properties of the wavelet that can be optimized analytically but whose influence on its real-world performance are not entirely understood. In this paper, a coevolutionary genetic algorithm is developed that searches the space of biorthogonal...

The paper proposes a wavelet-based forecasting method for time series. We used the multi-resolution decomposition of the signal implemented using trous wavelet transform. We combined the Stationary Wavelet Transform (SWT) with four prediction methodologies: Artificial Neural Networks, ARIMA, Linear regression and Random walk. These techniques were applied to two types of real data series: WiMAX...

As shown by Dahmen, Harbrecht and Schneider [7, 23, 32], the fully discrete wavelet Galerkin scheme for boundary integral equations scales linearly with the number of unknowns without compromising the accuracy of the underlying Galerkin scheme. The supposition is a wavelet basis with a sufficiently large number of vanishing moments. In this paper we present several constructions of appropriate ...

Let α > 0 and ψ (x) = x. Let Sn,α be a polynomial of degree n determined by the biorthogonality conditions Z 1 0 Sn,αψ j = 0, j = 0, 1, . . . , n− 1. We explicitly determine Sn,α and discuss some other properties, including their zero distribution. We also discuss their relation to the Sidi polynomials. §

We propose a model based approach for estimation of probability mass functions for discrete random variables. The model is based on tools from multirate signal processing. Similar in principle to the kernel based methods, the approach takes advantage of well-known results from multirate signal processing theory. Similarities to and differences from wavelet based appoaches is also indicated wher...

In this paper we construct compactly supported biorthogonal wavelet bases of the interval, with dilation factorM . Next, the natural MRA on the cube arising from the tensor product of a multilevel decomposition of the unit interval is developed. New Jackson and Bernstein type inequalities are proved, providing a characterization for anisotropic Sobolev spaces. AMS Subject Classification: 42C15.

Extending band-limited constructions of orthonormal refinable functions, a special class of periodic functions is used to generate a family of band-limited refinable functions. Characterizations of Riesz bases and frames formed by integer shifts of these refinable functions are obtained. Such families of refinable functions are employed to construct band-limited biorthogonal wavelet bases and b...

We present a parametrization of discrete finite biorthogonal wavelets with linear phase. Our approach is similar to Zou and Tewfik’s for orthogonal wavelets in the way that we utilize a lattice factorization of polyphase matrices of twochannel PR filter banks. However in the biorthogonal case we are faced with the additional possibilitiy of having length differences between the lowand high-pass...