A Bayesian Approach for Parameter Estimation in Railway Systems

被引：0

作者：

Jaoua, Nouha ^{[1
]}

Vanheeghe, Philippe ^{[1
,2
]}

Navarro, Nicolas ^{[1
]}

Langlois, Olivier ^{[3
]}

Iordache, Marius ^{[3
]}

机构：

[1] IRT Railenium, Valenciennes, France

[2] Univ Lille, CNRS, Cent Lille, UMR CRIStAL 9189, Lille, France

[3] Alstom, St Ouen, France

来源：

2018 4TH INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR SIGNAL AND IMAGE PROCESSING (ATSIP) | 2018年

基金：

欧盟地平线“2020”;

关键词：

parameter estimation; Expectation-Maximization algorithm; Sequential Monte Carlo methods; railway systems;

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 address the problem of parameter estimation in railway systems. For this purpose, a physical model of the train based on the fundamental principle of dynamics is proposed. Then, the parameter estimation is handled via an approach using a combination of Expectation-Maximization algorithm and Sequential Monte Carlo methods. The experiments performed both on synthetic and real data show the efficiency of the considered method.

引用

页数：6

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