Independent component analysis by wavelets

被引:0
|
作者
Pascal Barbedor
机构
[1] Université Paris VI et Université Paris VII,Laboratoire de Probabilités et Modéles Aléatoire CNRS
来源
TEST | 2009年 / 18卷
关键词
ICA; Wavelets; Besov spaces; Non parametric density estimation; 62H12; 62G05;
D O I
暂无
中图分类号
学科分类号
摘要
This paper introduces a new approach in solving the ICA problem using a method that fits in the contrast and minimize paradigm, mostly found in the ICA literature. In our case, the contrast is a L2 norm dependence measure, which constitutes an alternative to the usual criteria, based on mutual information. We propose a non parametric evaluation of the L2 contrast, using a wavelet projection estimator. The mean square error of the procedure is bounded under Besov assumptions. Finally, we provide a set of simulations to show how the method performs in practice.
引用
收藏
页码:136 / 155
页数:19
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