Gibbs random sequences Bayes estimation based on stochastic relaxation

V. Vasyukov, D. Goleshchikhin
{"title":"Gibbs random sequences Bayes estimation based on stochastic relaxation","authors":"V. Vasyukov, D. Goleshchikhin","doi":"10.1109/KORUS.2000.866016","DOIUrl":null,"url":null,"abstract":"An opportunity of Metropolis-Hastings stochastic relaxation procedure application for optimal Gibbs random message interpolation is investigated. A conditional-Gaussian random sequence as an example of Gibbs sequence observed in white Gaussian noise is used as message model. Such models are used, e.g. for speech signal description. The basic Metropolis-Hastings algorithm is described and some experimental results are presented.","PeriodicalId":20531,"journal":{"name":"Proceedings KORUS 2000. The 4th Korea-Russia International Symposium On Science and Technology","volume":"52 1","pages":"167-169 vol. 2"},"PeriodicalIF":0.0000,"publicationDate":"2000-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings KORUS 2000. The 4th Korea-Russia International Symposium On Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KORUS.2000.866016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

An opportunity of Metropolis-Hastings stochastic relaxation procedure application for optimal Gibbs random message interpolation is investigated. A conditional-Gaussian random sequence as an example of Gibbs sequence observed in white Gaussian noise is used as message model. Such models are used, e.g. for speech signal description. The basic Metropolis-Hastings algorithm is described and some experimental results are presented.
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
基于随机松弛的吉布斯随机序列贝叶斯估计
研究了Metropolis-Hastings随机松弛法应用于最优Gibbs随机信息插值的可能性。以条件高斯随机序列为例,以在高斯白噪声中观察到的吉布斯序列为消息模型。这样的模型被使用,例如用于语音信号描述。介绍了基本的Metropolis-Hastings算法,并给出了一些实验结果。
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
Influence of the shape factor on efficiency of the green compact ultrasonic compacting and properties of sintered zirconia ceramics Researching of rank detector on grayscale images Combustion of a coal particle with allowance for of environmental factor A control algorithm for voltage source converter in a system for generating AC power About knowledge representation and processing in intelligent systems
×
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