Wavelet thresholding for nonnecessarily Gaussian noise: functionality

Details Wavelet thresholding for nonnecessarily Gaussian noise: functionality Wavelet thresholding for nonnecessarily Gaussian noise: functionality

2006-02-11

arxiv.org/abs/math/0602241v1

Annals of Statistics 2005, Vol. 33, No. 5, 2164-2193

Mathematics

Statistics Theory

Published at http://dx.doi.org/10.1214/009053605000000471 in the Annals of Statistics (http://www.imstat.org/aos/) by the Inst

Scientific paper

10.1214/009053605000000471

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.

Affiliated with

Also associated with

No associations

Rating

Wavelet thresholding for nonnecessarily Gaussian noise: functionality does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Wavelet thresholding for nonnecessarily Gaussian noise: functionality, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Wavelet thresholding for nonnecessarily Gaussian noise: functionality will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-512803