This paper proposes a new methodology to compute Value at Risk (VaR) for quantifying losses in credit portfolios. We approximate the cumulative distribution of the loss function by a finite combination of Haar wavelets basis functions and calculate the coefficients of the approximation by inverting its Laplace transform. In fact, we demonstrate that only a few coefficients of the approximation ...

The aim of this paper is to study the multi-algorithm based palmprint indexing at feature extraction level. The proposed approach is based on the fusion of Haar wavelets and Zernike moments. Experiments are conducted on PolyU palmprint database to assess the actual advantage of the fusion of the multiple representations, in comparison to the single representation. Experimental results reveal th...

In this paper, we develop an accurate and ef£cient Haar wavelet method for well-known FitzHugh-Nagumo equation. The proposed scheme can be used to a wide class of nonlinear reaction-diffusion equations. The power of this manageable method is con£rmed. Moreover the use of Haar wavelets is found to be accurate, simple, fast, ¤exible, convenient, small computation costs and computationally attract...

Recently, the information processing approaches are increased. These methods can be used for several purposes: compressing, restoring, and information encoding. The raw data are less presented and are gradually replaced by others formats in terms of space or speed of access. This paper is interested in compression, precisely, the image compression using the Haar wavelets. The latter allows the ...

An orthonormal wavelet system in R, d ∈ N, is a countable collection of functions {ψ j,k}, j ∈ Z, k ∈ Z, ` = 1, . . . , L, of the form ψ j,k(x) = | deta|−j/2ψ`(a−jx− k) ≡ (Daj Tk ψ)(x) that is an orthonormal basis for L2(Rd), where a ∈ GLd(R) is an expanding matrix. The first such system to be discovered (almost one hundred years ago) is the Haar system for which L = d = 1, ψ1(x) = ψ(x) = χ[0,1...

The theory of periodic wavelet transforms presented here was originally developed to deal with the problem of epileptic seizure prediction. A central theorem in the theory is the characterization of wavelets having time and scale periodic wavelet transforms. In fact, we prove that such wavelets are precisely generalized Haar wavelets plus a logarithmic term. It became apparent that the aforemen...

In this work, a composite numerical scheme based on finite difference and Haar wavelets is proposed to solve time dependent coupled Burgers’ equation with appropriate initial and boundary conditions. Time derivative is discretized by forward difference and then quasilinearization technique is used to linearize the coupled Burgers’ equation. Space derivatives discretization with Haar wavelets le...

Abstract – This paper introduces some foundations of wavelets over Galois fields. Standard orthogonal finite-field wavelets (FFWavelets) including FF-Haar and FFDaubechies are derived. Non-orthogonal FFwavelets such as B-spline over GF(p) are also considered. A few examples of multiresolution analysis over Finite fields are presented showing how to perform Laplacian pyramid filtering of finite ...

In order to get an efficient image representation we introduce a new adaptive Haar wavelet transform, calledTetrolet Transform. Tetrolets are Haar-type wavelets whose supports are tetrominoes which are shapes made by connecting four equal-sized squares. The corresponding filter bank algorithm is simple but enormously effective. Numerical results show the strong efficiency of the tetrolet transf...

Investigation of various wavelet methods, for its capability of analyzing various dynamic phenomena through waves gained more and more attention in engineering research. Starting from ‘offering good solution to differential equations’ to capturing the nonlinearity in the data distribution, wavelets are used as appropriate tools that provide good mathematical model for scientific phenomena, whic...