非均匀性检测器的统计分析

M. Rangaswamy, B. Himed, J. Michels
{"title":"非均匀性检测器的统计分析","authors":"M. Rangaswamy, B. Himed, J. Michels","doi":"10.1109/ACSSC.2000.910688","DOIUrl":null,"url":null,"abstract":"We consider the statistical analysis of the recently proposed nonhomogeneity detector for Gaussian interference statistics. We show that a more stringent test can be constructed by accounting for the statistics of the generalized inner product (GIP) test under the condition of finite training data support. In particular, exact theoretical expressions for the GIP probability density function (PDF) and GIP mean are derived. Additionally, we show that for Gaussian interference statistics, the GIP admits a simple representation as the ratio of two statistically independent chi-square distributed random variables. Performance analysis of the more stringent GIP based test is presented.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"12 4 1","pages":"1117-1121 vol.2"},"PeriodicalIF":0.0000,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"Statistical analysis of the nonhomogeneity detector\",\"authors\":\"M. Rangaswamy, B. Himed, J. Michels\",\"doi\":\"10.1109/ACSSC.2000.910688\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider the statistical analysis of the recently proposed nonhomogeneity detector for Gaussian interference statistics. We show that a more stringent test can be constructed by accounting for the statistics of the generalized inner product (GIP) test under the condition of finite training data support. In particular, exact theoretical expressions for the GIP probability density function (PDF) and GIP mean are derived. Additionally, we show that for Gaussian interference statistics, the GIP admits a simple representation as the ratio of two statistically independent chi-square distributed random variables. Performance analysis of the more stringent GIP based test is presented.\",\"PeriodicalId\":10581,\"journal\":{\"name\":\"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)\",\"volume\":\"12 4 1\",\"pages\":\"1117-1121 vol.2\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACSSC.2000.910688\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.2000.910688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25

摘要

我们考虑了最近提出的高斯干涉统计的非均匀性检测器的统计分析。我们证明了在有限的训练数据支持下,利用广义内积(GIP)检验的统计量可以构造一个更严格的检验。特别地,导出了GIP概率密度函数(PDF)和GIP均值的精确理论表达式。此外,我们表明,对于高斯干涉统计,GIP允许一个简单的表示为两个统计独立的卡方分布随机变量的比率。对更严格的基于GIP的测试进行了性能分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical analysis of the nonhomogeneity detector
We consider the statistical analysis of the recently proposed nonhomogeneity detector for Gaussian interference statistics. We show that a more stringent test can be constructed by accounting for the statistics of the generalized inner product (GIP) test under the condition of finite training data support. In particular, exact theoretical expressions for the GIP probability density function (PDF) and GIP mean are derived. Additionally, we show that for Gaussian interference statistics, the GIP admits a simple representation as the ratio of two statistically independent chi-square distributed random variables. Performance analysis of the more stringent GIP based test is presented.
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
×
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:481959085
Book学术官方微信