Nonlinear L1 approximation of smooth functions

Huber Approximation for the Nonlinear l1 Problem

Nonlinear Approximation of Random Functions

Given an orthonormal basis and a certain class X of vectors in a Hilbert space H, consider the following nonlinear approximation process: approach a vector x ∈ X by keeping only its N largest coordinates, and let N go to infinity. In this paper, we study the accuracy of this process in the case where H = L(I), and we use either the trigonometric system or a wavelet basis to expand this space. T...

Smooth Reenable Functions Provide Good Approximation Orders Smooth Reenable Functions Provide Good Approximation Orders

We apply the general theory of approximation orders of shift-invariant spaces of BDR1-3] to the special case when the nitely many generators L 2 (IR d) of the underlying space S satisfy an N-scale relation (i.e., they form a \father wavelet" set). We show that the approximation orders provided by such nitely generated shift-invariant spaces are bounded from below by the smoothness class of each...

Approximation of Bivariate Functions via Smooth Extensions

For a smooth bivariate function defined on a general domain with arbitrary shape, it is difficult to do Fourier approximation or wavelet approximation. In order to solve these problems, in this paper, we give an extension of the bivariate function on a general domain with arbitrary shape to a smooth, periodic function in the whole space or to a smooth, compactly supported function in the whole ...

Approximation of smooth functions by neural networks

We review some aspects of our recent work on the approximation of functions by neural and generalized translation networks.