Solution of nonlinear Fredholm-Hammerstein integral equations by using semiorthogonal spline wavelets.
Solutions of time-varying singular nonlinear sytems by single-term Walsh series.
Solving the axisymmetric inverse heat conduction problem by a wavelet dual least squares method.
Sparse data structure design for wavelet-based methods
This course gives an introduction to the design of efficient datatypes for adaptive wavelet-based applications. It presents some code fragments and benchmark technics useful to learn about the design of sparse data structures and adaptive algorithms. Material and practical examples are given, and they provide good introduction for anyone involved in the development of adaptive applications. An answer will be given to the question: how to implement and efficiently use the discrete wavelet transform...
Sparse finite element methods for operator equations with stochastic data
Let be a strongly elliptic operator on a -dimensional manifold (polyhedra or boundaries of polyhedra are also allowed). An operator equation with stochastic data is considered. The goal of the computation is the mean field and higher moments , , , of the solution. We discretize the mean field problem using a FEM with hierarchical basis and degrees of freedom. We present a Monte-Carlo algorithm and a deterministic algorithm for the approximation of the moment for . The key tool...
Stability for nonlinear 2-D multiresolution: The approach of A. Harten.
Stable multiresolution analysis on triangles for surface compression.
Ternary wavelets and their applications to signal compression
We introduce ternary wavelets, based on an interpolating 4-point C^2 ternary stationary subdivision scheme, for compressing fractal-like signals. These wavelets are tightly squeezed and therefore they are more suitable for compressing fractal-like signals. The error in compressing fractal-like signals by ternary wavelets is at most half of that given by four-point wavelets (Wei and Chen, 2002). However, for compressing regular signals we further classify ternary wavelets into 'odd ternary' and 'even...
The integral wavelet transform in weighted Sobolev spaces.
The Mortar method in the wavelet context
This paper deals with the use of wavelets in the framework of the Mortar method. We first review in an abstract framework the theory of the mortar method for non conforming domain decomposition, and point out some basic assumptions under which stability and convergence of such method can be proven. We study the application of the mortar method in the biorthogonal wavelet framework. In particular we define suitable multiplier spaces for imposing weak continuity. Unlike in the classical mortar method,...
The Mortar Method in the Wavelet Context
This paper deals with the use of wavelets in the framework of the Mortar method. We first review in an abstract framework the theory of the mortar method for non conforming domain decomposition, and point out some basic assumptions under which stability and convergence of such method can be proven. We study the application of the mortar method in the biorthogonal wavelet framework. In particular we define suitable multiplier spaces for imposing weak continuity. Unlike in the classical mortar method,...
The partial inner product space method: a quick overview.
Time-dependent statistical analysis of wide-area time-synchronized data.
Two-dimensional Legendre wavelets and operational matrices of integration.
Valeurs des ondelettes aux bords d'un intervalle
Valuation of two-factor options under the Merton jump-diffusion model using orthogonal spline wavelets
This paper addresses the two-asset Merton model for option pricing represented by non-stationary integro-differential equations with two state variables. The drawback of most classical methods for solving these types of equations is that the matrices arising from discretization are full and ill-conditioned. In this paper, we first transform the equation using logarithmic prices, drift removal, and localization. Then, we apply the Galerkin method with a recently proposed orthogonal cubic spline-wavelet...
Wavelet bases for the biharmonic problem
In our contribution, we study different Riesz wavelet bases in Sobolev spaces based on cubic splines satisfying homogeneous Dirichlet boundary conditions of the second order. These bases are consequently applied to the numerical solution of the biharmonic problem and their quantitative properties are compared.
Wavelet clustering in time series analysis.
Wavelet compression of anisotropic integrodifferential operators on sparse tensor product spaces
For a class of anisotropic integrodifferential operators arising as semigroup generators of Markov processes, we present a sparse tensor product wavelet compression scheme for the Galerkin finite element discretization of the corresponding integrodifferential equations u = f on [0,1]n with possibly large n. Under certain conditions on , the scheme is of essentially optimal and dimension independent complexity (h-1| log h |2(n-1)) without corrupting the convergence or smoothness requirements...
Wavelet method for option pricing under the two-asset Merton jump-diffusion model
This paper examines the pricing of two-asset European options under the Merton model represented by a nonstationary integro-differential equation with two state variables. For its numerical solution, the wavelet-Galerkin method combined with the Crank-Nicolson scheme is used. A drawback of most classical methods is the full structure of discretization matrices. In comparison, the wavelet method enables the approximation of discretization matrices with sparse matrices. Sparsity is essential for the...