4.6 Review

Particle filtering without tears: A primer for beginners

期刊

COMPUTERS & CHEMICAL ENGINEERING
卷 95, 期 -, 页码 130-145

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2016.08.015

关键词

Monte Carlo method; Particle filter; State estimation; Bayesian inference

向作者/读者索取更多资源

The main purpose of this primer is to systematically introduce the theory of particle filters to readers with limited or no prior understanding of the subject. The primer is written for beginners and practitioners interested in learning about the theory and implementation of particle filtering methods. Throughout this primer we highlight the common mistakes that beginners and first-time researchers make in understanding and implementing the theory of particle filtering. We also discuss and demonstrate the use of particle filtering in nonlinear state estimation applications. We conclude the primer by providing an implementable version of MATLAB code for particle filters. The code not only aids in improving the understanding of particle filters, it also serves as a template for building and implementing advanced nonlinear state estimation routines. (C) 2016 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据