Wavelet Thresholding for Non Necessarily Gaussian Noise: Functionality
نویسنده
چکیده
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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