Deconvolution in white noise with a random blurring function

dc.creatorWiller, Thomas
dc.date2005-05-09
dc.date.accessioned2026-07-07T08:06:53Z
dc.date.available2026-07-07T08:06:53Z
dc.descriptionWe consider the problem of denoising a function observed after a convolution with a random filter independent of the noise and satisfying some mean smoothness condition depending on an ill posedness coefficient. We establish the minimax rates for the Lp risk over balls of periodic Besov spaces with respect to the level of noise, and we provide an adaptive estimator achieving these rates up to log factors. Simulations were performed to highlight the effects of the ill posedness and of the distribution of the filter on the efficiency of the estimator.
dc.identifierhttps://arxiv.org/abs/math/0505142
dc.identifierhttp://arxiv.org/abs/math/0505142
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130760
dc.subjectStatistics Theory
dc.subject62G05; 62G08; 62G20
dc.titleDeconvolution in white noise with a random blurring function
dc.typetext

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