关于复随机向量的最大熵定理

International Symposium on Information Theory and its Applications. International Symposium on Information Theory and its Applications Pub Date : 2004-01-01 DOI:10.1109/ISIT.2004.1365078

G. Tauböck

{"title":"关于复随机向量的最大熵定理","authors":"G. Tauböck","doi":"10.1109/ISIT.2004.1365078","DOIUrl":null,"url":null,"abstract":"This paper considers the complex random vectors and study some important properties. We develop a theory which is based on the concept of covariance and pseudo-covariance matrix in order to prove a stronger version of the maximum entropy theorem for the complex multivariate case (F.D. Neeser et al. 1993).","PeriodicalId":92224,"journal":{"name":"International Symposium on Information Theory and its Applications. International Symposium on Information Theory and its Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2004-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On the maximum entropy theorem for complex random vectors\",\"authors\":\"G. Tauböck\",\"doi\":\"10.1109/ISIT.2004.1365078\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper considers the complex random vectors and study some important properties. We develop a theory which is based on the concept of covariance and pseudo-covariance matrix in order to prove a stronger version of the maximum entropy theorem for the complex multivariate case (F.D. Neeser et al. 1993).\",\"PeriodicalId\":92224,\"journal\":{\"name\":\"International Symposium on Information Theory and its Applications. International Symposium on Information Theory and its Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on Information Theory and its Applications. International Symposium on Information Theory and its Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIT.2004.1365078\",\"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 Symposium on Information Theory and its Applications. International Symposium on Information Theory and its Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIT.2004.1365078","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

本文研究了复随机向量的一些重要性质。我们发展了一个基于协方差和伪协方差矩阵概念的理论，以证明复杂多元情况下最大熵定理的一个更强的版本(F.D. Neeser et al. 1993)。

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

微信好友朋友圈 QQ好友复制链接

本刊更多论文

On the maximum entropy theorem for complex random vectors

This paper considers the complex random vectors and study some important properties. We develop a theory which is based on the concept of covariance and pseudo-covariance matrix in order to prove a stronger version of the maximum entropy theorem for the complex multivariate case (F.D. Neeser et al. 1993).

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

International Symposium on Information Theory and its Applications. International Symposium on Information Theory and its Applications

自引率

0.00%

发文量

期刊最新文献

Rank Preserving Code-based Signature Buddhism and the Religious Other Statistical Inference and Exact Saddle Point Approximations Topological structures on DMC spaces A computer-aided investigation on the fundamental limits of caching