A stronger version of the redundancy-capacity theorem of universal coding

N. Merhav, M. Feder
{"title":"A stronger version of the redundancy-capacity theorem of universal coding","authors":"N. Merhav, M. Feder","doi":"10.1109/WITS.1994.513854","DOIUrl":null,"url":null,"abstract":"The capacity of the channel induced by a given class of sources is well known to be an attainable lower bound on the redundancy of universal codes w.r.t this class, both in the minimax sense and in the Bayesian (maximin) sense. We show that this capacity is essentially a lower bound also in a stronger sense, that is, for \"most\" sources in the class. This result extends Rissanen's lower bound for parametric families. We demonstrate its applicability in several examples and discuss its implications in statistical inference.","PeriodicalId":423518,"journal":{"name":"Proceedings of 1994 Workshop on Information Theory and Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1994 Workshop on Information Theory and Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WITS.1994.513854","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The capacity of the channel induced by a given class of sources is well known to be an attainable lower bound on the redundancy of universal codes w.r.t this class, both in the minimax sense and in the Bayesian (maximin) sense. We show that this capacity is essentially a lower bound also in a stronger sense, that is, for "most" sources in the class. This result extends Rissanen's lower bound for parametric families. We demonstrate its applicability in several examples and discuss its implications in statistical inference.
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
通用编码的冗余容量定理的更强版本
在极大极小和贝叶斯(极大极小)意义上,由一类给定的信源引起的信道容量是该类通用码冗余的可达到的下界。我们表明,这种能力本质上是一个下界,在更强的意义上,也就是说,对于类中的“大多数”源。这个结果推广了参数族的Rissanen下界。我们在几个例子中证明了它的适用性,并讨论了它在统计推断中的含义。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Large deviations and consistent estimates for Gibbs random fields Markov chains for modeling and analyzing digital data signals Maximized mutual information using macrocanonical probability distributions Coding for noisy feasible channels Identification via compressed data
×
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