卷积混合信号源盲分离的子空间方法

A. Mansour, C. Jutten, P. Loubaton
{"title":"卷积混合信号源盲分离的子空间方法","authors":"A. Mansour, C. Jutten, P. Loubaton","doi":"10.5281/ZENODO.35953","DOIUrl":null,"url":null,"abstract":"For the convolutive mixture, a subspace method to separate the sources is proposed. It is showed that after using only the second order statistic but more sensors than sources, the convolutive mixture can be itentified up to instantaneou mixture. Furthermore, the sources can be separated by any algorithm for instantaneous mixture (based in generally on the fourth order statistics).","PeriodicalId":282153,"journal":{"name":"1996 8th European Signal Processing Conference (EUSIPCO 1996)","volume":"343 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Subspace method for blind separation of sources in convolutive mixture\",\"authors\":\"A. Mansour, C. Jutten, P. Loubaton\",\"doi\":\"10.5281/ZENODO.35953\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the convolutive mixture, a subspace method to separate the sources is proposed. It is showed that after using only the second order statistic but more sensors than sources, the convolutive mixture can be itentified up to instantaneou mixture. Furthermore, the sources can be separated by any algorithm for instantaneous mixture (based in generally on the fourth order statistics).\",\"PeriodicalId\":282153,\"journal\":{\"name\":\"1996 8th European Signal Processing Conference (EUSIPCO 1996)\",\"volume\":\"343 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1996 8th European Signal Processing Conference (EUSIPCO 1996)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5281/ZENODO.35953\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1996 8th European Signal Processing Conference (EUSIPCO 1996)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/ZENODO.35953","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

摘要

对于卷积混合信号,提出了一种子空间分离方法。结果表明,在只使用二阶统计量,传感器多于源的情况下,卷积混合可以被识别到瞬时混合。此外,源可以通过任何算法进行瞬时混合(通常基于四阶统计量)分离。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Subspace method for blind separation of sources in convolutive mixture
For the convolutive mixture, a subspace method to separate the sources is proposed. It is showed that after using only the second order statistic but more sensors than sources, the convolutive mixture can be itentified up to instantaneou mixture. Furthermore, the sources can be separated by any algorithm for instantaneous mixture (based in generally on the fourth order statistics).
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
期刊最新文献
PDF Not Yet Available In IEEE Xplore Parameter estimation of exponentially damped sinusoids using second order statistics A multivariable Steiglitz-McBride method On the approximation of nonbandlimited signals by nonuniform sampling series Model reduction by Kautz filters
×
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