AbstractWavelet 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 repres...
International audienceThis note is devoted to an analysis of the so-called peeling algorithm in wave...
AbstractNonlinear thresholding of wavelet coefficients is an efficient method for denoising signals ...
In standard wavelet methods, the empirical wavelet coefficients are thresholded term by term, on the...
AbstractThe almost everywhere convergence of wavelet series is important in wavelet analysis [S. Kel...
AbstractWavelet shrinkage estimators are obtained by applying a shrinkage rule on the empirical wave...
AbstractWavelet shrinkage is a strategy to obtain a nonlinear approximation to a given signal and is...
International audienceThis work addresses the unification of some basic functions and thresholds use...
AbstractIn the paper minimax rates of convergence for wavelet estimators are studied. The estimators...
With this article we first like to give a brief review on wavelet thresholding methods in non-Gaussi...
With this article we first like to give a brief review on wavelet thresholding methods in non-Gaussi...
We propose a model to reconstruct wavelet coefficients using a total variation minimization algorith...
AbstractThe wavelet threshold estimator of a regression function for the random design is constructe...
International audienceThis note is devoted to an analysis of the so-called peeling algorithm in wave...
Density estimation is a commonly used test case for non-parametric estimation methods. We explore th...
We consider a block thresholding and vaguelet–wavelet approach to certain statistical linear inverse...
International audienceThis note is devoted to an analysis of the so-called peeling algorithm in wave...
AbstractNonlinear thresholding of wavelet coefficients is an efficient method for denoising signals ...
In standard wavelet methods, the empirical wavelet coefficients are thresholded term by term, on the...
AbstractThe almost everywhere convergence of wavelet series is important in wavelet analysis [S. Kel...
AbstractWavelet shrinkage estimators are obtained by applying a shrinkage rule on the empirical wave...
AbstractWavelet shrinkage is a strategy to obtain a nonlinear approximation to a given signal and is...
International audienceThis work addresses the unification of some basic functions and thresholds use...
AbstractIn the paper minimax rates of convergence for wavelet estimators are studied. The estimators...
With this article we first like to give a brief review on wavelet thresholding methods in non-Gaussi...
With this article we first like to give a brief review on wavelet thresholding methods in non-Gaussi...
We propose a model to reconstruct wavelet coefficients using a total variation minimization algorith...
AbstractThe wavelet threshold estimator of a regression function for the random design is constructe...
International audienceThis note is devoted to an analysis of the so-called peeling algorithm in wave...
Density estimation is a commonly used test case for non-parametric estimation methods. We explore th...
We consider a block thresholding and vaguelet–wavelet approach to certain statistical linear inverse...
International audienceThis note is devoted to an analysis of the so-called peeling algorithm in wave...
AbstractNonlinear thresholding of wavelet coefficients is an efficient method for denoising signals ...
In standard wavelet methods, the empirical wavelet coefficients are thresholded term by term, on the...