AbstractWe present a new method for the approximation of Wiener integrals and provide an explicit error bound for a class F of smooth integrands. The purely deterministic algorithm is a sequence of quadrature formulas for the Wiener measure, where the knots are piecewise linear functions. It uses ideas of Smolyak, as well as the multiscale decomposition of the Wiener measure due to Lévy and Ciesielski. For the class F we obtain n(ε)⩽max(1, 2ε−4), where n(ε) is the number of integrand evaluations needed to guarantee an error at most ε for f∈F
AbstractWe analyze the complexity of nonlinear Lebesgue integration problems in the average case set...
There exist many numerical methods for numerical solutions of the systems of stochastic differential...
We study average case approximation of Euler and Wiener integrated processes of d variables which a...
. We propose isotropic probability measures defined on classes of smooth multivariate functions. The...
AbstractWe study the average case complexity of multivariate integration and L2 function approximati...
AbstractWe study the average case complexity of multivariate integration and L2 function approximati...
AbstractWe study probabilistic properties of Simpson′s quadrature, assuming that the class of integr...
AbstractWe study probabilistic properties of Simpson′s quadrature, assuming that the class of integr...
AbstractIn this paper, we study the approximation of the identity operator and the integral operator...
AbstractIn this paper, we study the approximation of the identity operator and the integral operator...
We study average case approximation of Euler and Wiener integrated processes of d variables which a...
AbstractNew approximation formulas with weight for the functional integrals with conditional Wiener ...
Given a probability measure ν and a positive integer n. How to choose n knots and n weights such tha...
AbstractThe n-widths of a subset A of a Banach space B describe how well the elements of A can be ap...
AbstractThis paper introduces a measure of accuracy for quadrature methods for Fredholm integral equ...
AbstractWe analyze the complexity of nonlinear Lebesgue integration problems in the average case set...
There exist many numerical methods for numerical solutions of the systems of stochastic differential...
We study average case approximation of Euler and Wiener integrated processes of d variables which a...
. We propose isotropic probability measures defined on classes of smooth multivariate functions. The...
AbstractWe study the average case complexity of multivariate integration and L2 function approximati...
AbstractWe study the average case complexity of multivariate integration and L2 function approximati...
AbstractWe study probabilistic properties of Simpson′s quadrature, assuming that the class of integr...
AbstractWe study probabilistic properties of Simpson′s quadrature, assuming that the class of integr...
AbstractIn this paper, we study the approximation of the identity operator and the integral operator...
AbstractIn this paper, we study the approximation of the identity operator and the integral operator...
We study average case approximation of Euler and Wiener integrated processes of d variables which a...
AbstractNew approximation formulas with weight for the functional integrals with conditional Wiener ...
Given a probability measure ν and a positive integer n. How to choose n knots and n weights such tha...
AbstractThe n-widths of a subset A of a Banach space B describe how well the elements of A can be ap...
AbstractThis paper introduces a measure of accuracy for quadrature methods for Fredholm integral equ...
AbstractWe analyze the complexity of nonlinear Lebesgue integration problems in the average case set...
There exist many numerical methods for numerical solutions of the systems of stochastic differential...
We study average case approximation of Euler and Wiener integrated processes of d variables which a...