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Februrary 2003 Wavelet thresholding for non-necessarily Gaussian noise: idealism
R. Averkamp, C. Houdré
Ann. Statist. 31(1): 110-151 (Februrary 2003). DOI: 10.1214/aos/1046294459

Abstract

For various types of noise (exponential, normal mixture, compactly supported, ...) wavelet thresholding methods are studied. Problems linked to the existence of optimal thresholds are tackled, and minimaxity properties of the methods also analyzed. A coefficient dependent method for choosing thresholds is also briefly presented.

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R. Averkamp. C. Houdré. "Wavelet thresholding for non-necessarily Gaussian noise: idealism." Ann. Statist. 31 (1) 110 - 151, Februrary 2003. https://doi.org/10.1214/aos/1046294459

Information

Published: Februrary 2003
First available in Project Euclid: 26 February 2003

zbMATH: 1102.62329
MathSciNet: MR1962501
Digital Object Identifier: 10.1214/aos/1046294459

Subjects:
Primary: 62C20, 62G07
Secondary: 41A25, 60G70

Rights: Copyright © 2003 Institute of Mathematical Statistics

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Vol.31 • No. 1 • Februrary 2003
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