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Wavelet thresholding for nonnecessarily Gaussian noise: functionality

R. Averkamp·C. Houdré
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Abstract

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 are also briefly discussed.

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R. Averkamp, C. Houdré. 2006-02-11. Wavelet thresholding for nonnecessarily Gaussian noise: functionality. https://doi.org/10.1214/009053605000000471

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