A temporal reasoning method based on maximum a posteriori estimation in situation assessment

Yao Chunyan, Yu Wenxian, Zhu Zhaowen
{"title":"A temporal reasoning method based on maximum a posteriori estimation in situation assessment","authors":"Yao Chunyan, Yu Wenxian, Zhu Zhaowen","doi":"10.1109/NAECON.1998.710179","DOIUrl":null,"url":null,"abstract":"Stochastic temporal reasoning in situation assessment (SA) is very important in many applications. The approach based on Maximum Likelihood Estimation (MLE) treats the unknown temporal variable as a constant which doesn't use a priori information and generates a larger estimate variance. In this paper, the relation model of known temporal information and unknown temporal variable has been established which can also be used to MLE-based method. In the model, the forward and backward reasoning algorithm about time instants has been derived by treating the unknown temporal variable as random variable and introducing MAP estimation into temporal reasoning. The performance analysis between MAP-based method and MLE-based method shows that under some conditions, the estimate variance of MAP-based method is lower than MLE-based method, and we have given these conditions by experiments.","PeriodicalId":202280,"journal":{"name":"Proceedings of the IEEE 1998 National Aerospace and Electronics Conference. NAECON 1998. Celebrating 50 Years (Cat. No.98CH36185)","volume":"36 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE 1998 National Aerospace and Electronics Conference. NAECON 1998. Celebrating 50 Years (Cat. No.98CH36185)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAECON.1998.710179","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Stochastic temporal reasoning in situation assessment (SA) is very important in many applications. The approach based on Maximum Likelihood Estimation (MLE) treats the unknown temporal variable as a constant which doesn't use a priori information and generates a larger estimate variance. In this paper, the relation model of known temporal information and unknown temporal variable has been established which can also be used to MLE-based method. In the model, the forward and backward reasoning algorithm about time instants has been derived by treating the unknown temporal variable as random variable and introducing MAP estimation into temporal reasoning. The performance analysis between MAP-based method and MLE-based method shows that under some conditions, the estimate variance of MAP-based method is lower than MLE-based method, and we have given these conditions by experiments.
一种基于最大后验估计的态势评估时间推理方法
态势评估中的随机时间推理在许多应用中都是非常重要的。基于极大似然估计(MLE)的方法将未知的时间变量视为一个常数,不使用先验信息,产生更大的估计方差。本文建立了已知时间信息与未知时间变量之间的关系模型,该模型也可用于基于mle的方法。在该模型中,将未知时间变量视为随机变量,并将MAP估计引入到时间推理中,推导了时间瞬间的正反向推理算法。通过对基于map的方法和基于mle的方法的性能分析表明,在某些条件下,基于map的方法的估计方差小于基于mle的方法,并通过实验给出了这些条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信