大学生卡尔曼滤波教程

M. Rhudy, R. Salguero, Keaton Holappa
{"title":"大学生卡尔曼滤波教程","authors":"M. Rhudy, R. Salguero, Keaton Holappa","doi":"10.5121/IJCSES.2017.8101","DOIUrl":null,"url":null,"abstract":"This paper presents a tutorial on Kalman filtering that is designed for instruction to undergraduate students. The idea behind this work is that undergraduate students do not have much of the statistical and theoretical background necessary to fully understand the existing research papers and textbooks on this topic. Instead, this work offers an introductory experience for students which takes a more practical usage perspective on the topic, rather than the statistical derivation. Students reading this paper should be able to understand how to apply Kalman filtering tools to mathematical problems without requiring a deep theoretical understanding of statistical theory.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"203 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"63","resultStr":"{\"title\":\"A Kalman Filtering Tutorial for Undergraduate Students\",\"authors\":\"M. Rhudy, R. Salguero, Keaton Holappa\",\"doi\":\"10.5121/IJCSES.2017.8101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a tutorial on Kalman filtering that is designed for instruction to undergraduate students. The idea behind this work is that undergraduate students do not have much of the statistical and theoretical background necessary to fully understand the existing research papers and textbooks on this topic. Instead, this work offers an introductory experience for students which takes a more practical usage perspective on the topic, rather than the statistical derivation. Students reading this paper should be able to understand how to apply Kalman filtering tools to mathematical problems without requiring a deep theoretical understanding of statistical theory.\",\"PeriodicalId\":415526,\"journal\":{\"name\":\"International Journal of Computer Science & Engineering Survey\",\"volume\":\"203 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-02-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"63\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computer Science & Engineering Survey\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/IJCSES.2017.8101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer Science & Engineering Survey","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/IJCSES.2017.8101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 63

摘要

本文介绍了一个卡尔曼滤波的教程,它是为本科生设计的。这项工作背后的想法是,本科生没有太多必要的统计和理论背景,以充分理解现有的研究论文和教科书关于这个主题。相反,这项工作为学生提供了一个介绍性的经验,它对这个主题采取了更实际的使用角度,而不是统计推导。阅读本文的学生应该能够理解如何将卡尔曼滤波工具应用于数学问题,而不需要对统计理论有深刻的理论理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A Kalman Filtering Tutorial for Undergraduate Students
This paper presents a tutorial on Kalman filtering that is designed for instruction to undergraduate students. The idea behind this work is that undergraduate students do not have much of the statistical and theoretical background necessary to fully understand the existing research papers and textbooks on this topic. Instead, this work offers an introductory experience for students which takes a more practical usage perspective on the topic, rather than the statistical derivation. Students reading this paper should be able to understand how to apply Kalman filtering tools to mathematical problems without requiring a deep theoretical understanding of statistical theory.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Barriers for Females to Pursue Stem Careers and Studies at Higher Education Institutions (HEI). A Closer Look at Academic Literature 5G Vs Wi-Fi Indoor Positioning: A Comparative Study Advance in Image and Audio Restoration and their Assessments: A Review Multilayer Backpropagation Neural Networks for Implementation of Logic Gates Artificial Neural Networks for Medical Diagnosis: A Review of Recent Trends
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1