实复正态分布

A. Bos
{"title":"实复正态分布","authors":"A. Bos","doi":"10.1109/18.681349","DOIUrl":null,"url":null,"abstract":"An expression is derived for the distribution of a mixture of real and complex normal variates. The asymptotic distribution of the resulting real-complex maximum-likelihood estimates is the real-complex normal distribution derived. The covariance matrix of this distribution is particularly important. It is the asymptotic covariance matrix for maximum-likelihood estimates and the Cramer-Rao lower bound on the variance of the real-complex estimates in general. From this covariance matrix, the variance of the reconstructed complex-valued exit wave then follows using the pertinent propagation formulas. The resulting expressions show the dependence of the variance on the free microscope parameters used for experimental design.","PeriodicalId":13250,"journal":{"name":"IEEE Trans. Inf. Theory","volume":"76 1","pages":"1670-1672"},"PeriodicalIF":0.0000,"publicationDate":"1998-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"The Real-Complex Normal Distribution\",\"authors\":\"A. Bos\",\"doi\":\"10.1109/18.681349\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An expression is derived for the distribution of a mixture of real and complex normal variates. The asymptotic distribution of the resulting real-complex maximum-likelihood estimates is the real-complex normal distribution derived. The covariance matrix of this distribution is particularly important. It is the asymptotic covariance matrix for maximum-likelihood estimates and the Cramer-Rao lower bound on the variance of the real-complex estimates in general. From this covariance matrix, the variance of the reconstructed complex-valued exit wave then follows using the pertinent propagation formulas. The resulting expressions show the dependence of the variance on the free microscope parameters used for experimental design.\",\"PeriodicalId\":13250,\"journal\":{\"name\":\"IEEE Trans. Inf. Theory\",\"volume\":\"76 1\",\"pages\":\"1670-1672\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Trans. Inf. Theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/18.681349\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Trans. Inf. Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/18.681349","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

摘要

导出了实正态变量和复正态变量混合分布的表达式。所得到的实复最大似然估计的渐近分布是导出的实复正态分布。这个分布的协方差矩阵尤为重要。它是极大似然估计的渐近协方差矩阵和一般实复估计方差的Cramer-Rao下界。根据协方差矩阵,利用相应的传播公式,得到重构的复值出口波的方差。所得表达式显示了方差与实验设计所用自由显微镜参数的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Real-Complex Normal Distribution
An expression is derived for the distribution of a mixture of real and complex normal variates. The asymptotic distribution of the resulting real-complex maximum-likelihood estimates is the real-complex normal distribution derived. The covariance matrix of this distribution is particularly important. It is the asymptotic covariance matrix for maximum-likelihood estimates and the Cramer-Rao lower bound on the variance of the real-complex estimates in general. From this covariance matrix, the variance of the reconstructed complex-valued exit wave then follows using the pertinent propagation formulas. The resulting expressions show the dependence of the variance on the free microscope parameters used for experimental design.
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