Wavelet thresholding for nonnecessarily Gaussian noise: Functionality
نویسندگان
چکیده
منابع مشابه
Wavelet Thresholding for Non Necessarily Gaussian Noise: Functionality
For signals belonging to balls in smoothness classes and noise with enough moments, the asymptotic behavior of the minimax quadratic risk among soft–threshold estimates is investigated. In turn, these results combined with a median filtering method lead to asymptotics for denoising heavy tails via wavelet thresholding. Some further comparisons of wavelet thresholding and of kernel estimators ar...
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For various types of noise (exponential, normal mixture, compactly supported, ...) wavelet tresholding 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. 1. Introduction. A common underlying assumption in non-parametric c...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2005
ISSN: 0090-5364
DOI: 10.1214/009053605000000471