The approximation of a function affected by noise in several dimensions suffers from the so called curse of dimensionality. In this paper a Fourier series method based on regularization is developed both for uniform and random design when a restriction on the complexity of the curve such as additivity is considered
Fourier series estimation in separable models
De Feis I
2002
Abstract
The approximation of a function affected by noise in several dimensions suffers from the so called curse of dimensionality. In this paper a Fourier series method based on regularization is developed both for uniform and random design when a restriction on the complexity of the curve such as additivity is consideredFile in questo prodotto:
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