Convergence of wavelet thresholding estimators of differential operators

  • Di Rong Chen*
  • , Hongtao Meng
  • *Corresponding author for this work

Research output: Contribution to journalLetterpeer-review

Abstract

Wavelet shrinkage is a strategy to obtain a nonlinear approximation to a given signal. The shrinkage method is applied in different areas, including data compression, signal processing and statistics. The almost everywhere convergence of resulting wavelet series has been established in [T. Tao, On the almost everywhere convergence of wavelet summation methods, Appl. Comput. Harmon. Anal. 3 (1996) 384-387] and [T. Tao, B. Vidakovic, Almost everywhere behavior of general wavelet shrinkage operators, Appl. Comput. Harmon. Anal. 9 (2000) 72-82]. With a representation of f in terms of wavelet coefficients of f, we are interested in considering the influence of wavelet thresholding to f on its derivative f. In this paper, for the representation of differential operators in nonstandard form, we establish the almost everywhere convergence of estimators as threshold tends to zero.

Original languageEnglish
Pages (from-to)266-275
Number of pages10
JournalApplied and Computational Harmonic Analysis
Volume25
Issue number2
DOIs
StatePublished - Sep 2008

Keywords

  • Hardy-Littlewood maximal function
  • Nonstandard form
  • Thresholding
  • Wavelets

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