ADAPTIVE LINEAR PREDICTION FILTERS BASED ON MAXIMUM A POSTERIORI ESTIMATION

被引：0

作者：

Andersen, Kristian T. ^{[1
,2
]}

van Waterschoot, Toon ^{[1
]}

Moonen, Marc ^{[1
]}

机构：

[1] Katholieke Univ Leuven, ESAT STADIUS, Kasteelpk Arenberg 10, B-3001 Louvain, Belgium

[2] Widex AS, Nymollevej 6, DK-3540 Lynge, Denmark

来源：

2015 23RD EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO) | 2015年

关键词：

Maximum a posteriori; adaptive filters; linear prediction; regularization; adaptive line enhancer;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we develop adaptive linear prediction filters in the framework of maximum a posteriori (MAP) estimation. It is shown how priors can be used to regularize the solution and references to known algorithms are made. The adaptive filters are suitable for implementation in real-time and by simulation with an adaptive line enhancer (ALE), it is shown how the parameters of the estimation problem affect the convergence of the adaptive filter. The adaptive line enhancer (ALE) is a widely used adaptive filler to separate periodic signals from additive background noise where it has traditionally been implemented using the least-mean-square (LMS) or recursive least-square (RLS) filter. The derived algorithms can generally be used in any adaptive filter application with a desired target signal.

引用

页码：2706 / 2710

页数：5

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