论文检索

基于最大似然的多尺度方差稳定化AI 解读

This article proposes maximum likelihood approaches for multiscale variance stabilization transformations for independently and identically distributed data. For two multiscale variance stabilization transformations we present new unified theoretical results on their Jacobians, a key component of the likelihood. The results provide a deeper understanding of the transformations and the ability to compute the likelihood in linear time. The transformations are shown empirically…

使用交叉验证的小波收缩AI 解读

SUMMARY Wavelets are orthonormal basis functions with special properties that show potential in many areas of mathematics and statistics. This paper concentrates on the estimation of functions and images from noisy data by using wavelet shrinkage. A modified form of twofold cross-validation is introduced to choose a threshold for wavelet shrinkage estimators operating on data sets of length a power of 2. The cross-validation algorithm is then extended to data sets of any…