Approximation

Research into self-regulated learning has traditionally relied upon self-reported data. While there is a rich body of literature… Expand

Meshfree approximation methods are a relatively new area of research, and there are only a few books covering it at present… Expand

Preface Part I. Introduction: 1. Introduction 2. Motivating examples Part II. Preliminaries: 3. Tools from matrix theory 4… Expand

1. Applications and motivations 2. Hear spaces and multivariate polynomials 3. Local polynomial reproduction 4. Moving least… Expand

BASIC THEORY 1.1 Orthogonal polynomials 1.2 Properties of orthogonal polynomials 1.3 Three-term recurrence relation 1.4… Expand

We generalize the notion of an approximation space introduced in [8]. In tolerance approximation spaces we define the lower and… Expand

Subspace estimation plays an important role in a variety of modern signal processing applications. We present a new approach for… Expand

In this paper we demonstrate that finite linear combinations of compositions of a fixed, univariate function and a set of affine… Expand

Abstract We show that standard multilayer feedforward networks with as few as a single hidden layer and arbitrary bounded and… Expand

The problem of the approximation of nonlinear mapping, (especially continuous mappings) is considered. Regularization theory and… Expand