A PROBABILISTIC LEAST-MEAN-SQUARES FILTER

被引：0

作者：

Fernandez-Bes, Jesus ^{[1
]}

Elvira, Victor ^{[1
]}

Van Vaerenbergh, Steven ^{[2
]}

机构：

[1] Univ Carlos III Madrid, Dept Signal Theory & Commun, Leganes, Spain

[2] Univ Cantabria, Dept Commun Engn, Santander, Spain

来源：

2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP) | 2015年

关键词：

probabilistic models; least-mean-squares; adaptive filtering; state-space models; TUTORIAL;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

We introduce a probabilistic approach to the LMS filter. By means of an efficient approximation, this approach provides an adaptable step-size LMS algorithm together with a measure of uncertainty about the estimation. In addition, the proposed approximation preserves the linear complexity of the standard LMS. Numerical results show the improved performance of the algorithm with respect to standard LMS and state-of-the-art algorithms with similar complexity. The goal of this work, therefore, is to open the door to bring some more Bayesian machine learning techniques to adaptive filtering.

引用

页码：2199 / 2203

页数：5

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