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Data fitting by wavelet shrinkage using GM-waves

Abstract

We study data-fitting methods based on wavelet shrinkage. We discuss several methods for threshold and non-treshold shrinkage of the wavelet coefficients, and compare their performance for the model problems of non-parametric regression and density estimation, under the assumption of Besov regularity of the estimated function. The results are illustrated by graphical visualization of several numerical examples, using the new wavelet-based modelling and visualization library GM-waves.

Category

Academic chapter

Language

English

Author(s)

  • Tatiana N. Moguchaya
  • Joakim Gundersen
  • Niklas Grip
  • Lubomir T. Dechevski
  • Børre Bang
  • Arne Lakså
  • Ewald Gunther Quak
  • Bowei Tong

Affiliation

  • SINTEF Digital / Mathematics and Cybernetics
  • Luleå University of Technology
  • UiT The Arctic University of Norway

Year

2005

Publisher

Nashboro Press

Book

Mathematical Methods for Curves and Surfaces: Tromsø 2004

ISBN

9780972848244

Page(s)

263 - 274

View this publication at Norwegian Research Information Repository