Multiple shrinkage and subset selection in wavelets
小波中的多重收缩与子集选择
This paper discusses Bayesian methods for multiple shrinkage estimation in wavelets. Wavelets are used in applications for data denoising, via shrinkage of the coefficients towards zero, and for data compression, by shrinkage and setting small coefficients to zero. We approach wavelet shrinkage by using Bayesian hierarchical models, assigning a positive prior probability to the wavelet coefficients king zero. The resulting estimator for the wavelet coefficients is a multiple…