Accurate Gaussian Mixture Model Smoothing using a Two-Filter Approach

被引：0

作者：

Balenzuela, Mark P. ^{[1
]}

Dahlin, Johan ^{[1
]}

Bartlett, Nathan ^{[1
]}

Wills, Adrian G. ^{[1
]}

Renton, Christopher ^{[1
]}

Ninness, Brett ^{[1
]}

机构：

[1] Univ Newcastle, Fac Engn & Built Environm, Callaghan, NSW, Australia

来源：

2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2018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：

We present a general and computationally tractable method for the operation of a Backwards Information Filter on a linear Gaussian Mixture Model system, which can be used to generate the smoothed density. Unlike other methods, the algorithm proposed here does not make unimodal approximations, and is exact with the exception of the mode reduction strategy.

引用

页码：694 / 699

页数：6

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