Gamma-Minimax Wavelet Shrinkage: A Robust Incorporation of Information about Energy of a Signal in Denoising Applications (Articolo in rivista)

Type
Label
  • Gamma-Minimax Wavelet Shrinkage: A Robust Incorporation of Information about Energy of a Signal in Denoising Applications (Articolo in rivista) (literal)
Anno
  • 2004-01-01T00:00:00+01:00 (literal)
Alternative label
  • Angelini C.; Vidakovic B. (2004)
    Gamma-Minimax Wavelet Shrinkage: A Robust Incorporation of Information about Energy of a Signal in Denoising Applications
    in Statistica sinica
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Angelini C.; Vidakovic B. (literal)
Pagina inizio
  • 103 (literal)
Pagina fine
  • 124 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www3.stat.sinica.edu.tw/statistica/oldpdf/A14n14.pdf (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 14 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 1 (literal)
Note
  • Scopu (literal)
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Istituto per le Applicazioni del Calcolo -Sezione di Napoli and Georgia Institute of Technology (literal)
Titolo
  • Gamma-Minimax Wavelet Shrinkage: A Robust Incorporation of Information about Energy of a Signal in Denoising Applications (literal)
Abstract
  • In this paper we propose a method for wavelet filtering of noisy signals when prior information about the L2 energy of the signal of interest is available? Assuming the independence model? according to which the wavelet coe?cients are treated individually? we propose a level dependent shrinkage rule that turns out to be the ??minimax rule for a suitable class? say ?? of realistic priors on the wavelet coe?cients? The proposed methodology is particularly well suited for denoising tasks where signal?to?noise ratio is low? and it is illustrated on a battery of standard test function tions? Performance comparisons with some others methods existing in the literature are provided? An example in atomic force microscopy ?AFM? is also discussed? Key words and phrases? Atomic force microscopy? bounded normal mean? ??mini? maxity? shrinkage? wavelet regression? (literal)
Prodotto di
Autore CNR
Insieme di parole chiave

Incoming links:


Prodotto
Autore CNR di
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi
Insieme di parole chiave di
data.CNR.it