{"title":"基于同时张量对角化的I.I.D.信号卷积分离","authors":"S. Rhioui, E. Moreau","doi":"10.1109/SPAWC.2006.346340","DOIUrl":null,"url":null,"abstract":"This paper considers the problem of blind separation of a MIMO convolutive mixture of i.i.d. source signals. Separation criteria are considered for the overall extraction of source signals according to the use of so-called reference signals. We present a new MIMO contrast function using reference signals, which is moreover seen to have joint-diagonalization interpretation. A link with the PARAFAC decomposition is also emphasized. Finally the performance are investigated through computer simulations","PeriodicalId":414942,"journal":{"name":"2006 IEEE 7th Workshop on Signal Processing Advances in Wireless Communications","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Convolutive Separation of I.I.D. Signals Based on Simultaneous Tensors Diagonalization\",\"authors\":\"S. Rhioui, E. Moreau\",\"doi\":\"10.1109/SPAWC.2006.346340\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper considers the problem of blind separation of a MIMO convolutive mixture of i.i.d. source signals. Separation criteria are considered for the overall extraction of source signals according to the use of so-called reference signals. We present a new MIMO contrast function using reference signals, which is moreover seen to have joint-diagonalization interpretation. A link with the PARAFAC decomposition is also emphasized. Finally the performance are investigated through computer simulations\",\"PeriodicalId\":414942,\"journal\":{\"name\":\"2006 IEEE 7th Workshop on Signal Processing Advances in Wireless Communications\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE 7th Workshop on Signal Processing Advances in Wireless Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPAWC.2006.346340\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE 7th Workshop on Signal Processing Advances in Wireless Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAWC.2006.346340","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Convolutive Separation of I.I.D. Signals Based on Simultaneous Tensors Diagonalization
This paper considers the problem of blind separation of a MIMO convolutive mixture of i.i.d. source signals. Separation criteria are considered for the overall extraction of source signals according to the use of so-called reference signals. We present a new MIMO contrast function using reference signals, which is moreover seen to have joint-diagonalization interpretation. A link with the PARAFAC decomposition is also emphasized. Finally the performance are investigated through computer simulations