Unsupervised signal restoration using copulas and pairwise Markov chains

被引：0

作者：

Brunel, N ^{[1
]}

Pieczynski, W ^{[1
]}

机构：

[1] CNRS UMR 5157, GET INT Dept CITI, F-91000 Evry, France

来源：

PROCEEDINGS OF THE 2003 IEEE WORKSHOP ON STATISTICAL SIGNAL PROCESSING | 2003年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This work is about the statistical restoration of hidden discrete signals. The problem we deal with is how to take into account, in recent pairwise and triplet Markov chain context, complex noises that can be non-Gaussian, correlated, and of class-varying nature. We propose to solve this modeling problem using Copulas. The interest of the new modeling is validated by experiments performed in supervised and unsupervised context. In the latter, all parameters are estimated from the only observed data by an original method.

引用

页码：102 / 105

页数：4

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