Wavelet thresholding for non-necessarily Gaussian noise: idealism

Averkamp, R.; Houdré, C.

Ann. Statist., Tome 31 (2003) no. 1, p. 110-151 / Harvested from Project Euclid

Résumé

For various types of noise (exponential, normal mixture, compactly supported, ...) wavelet thresholding 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.

Publié le : 2003-02-14
Classification: Wavelets, thresholding, minimax, 62G07, 62C20, 60G70, 41A25

@article{1046294459,
     author = {Averkamp, R. and Houdr\'e, C.},
     title = {Wavelet thresholding for non-necessarily Gaussian noise: idealism},
     journal = {Ann. Statist.},
     volume = {31},
     number = {1},
     year = {2003},
     pages = { 110-151},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1046294459}
}

Averkamp, R.; Houdré, C. Wavelet thresholding for non-necessarily Gaussian noise: idealism. Ann. Statist., Tome 31 (2003) no. 1, pp.  110-151. http://gdmltest.u-ga.fr/item/1046294459/