{"title":"基于parafac的4阶累积量盲信道识别","authors":"C. Fernandes, G. Favier, J. Mota","doi":"10.1109/ITS.2006.4433376","DOIUrl":null,"url":null,"abstract":"Strong relationships between joint- diagonalization and tensor decompositions have been established recently. In this paper we propose a finite impulse response (FIR) channel identification method based on the Parafac decomposition of a 3rd-order tensor composed of the 4-th order output cumulants. By avoiding the prewhitening operation required by joint-diagonalization based methods, our method is shown to improve the estimation performance provided by the classic joint-diagonalization algorithm.","PeriodicalId":271294,"journal":{"name":"2006 International Telecommunications Symposium","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Parafac-based blind channel identification using 4th-order cumulants\",\"authors\":\"C. Fernandes, G. Favier, J. Mota\",\"doi\":\"10.1109/ITS.2006.4433376\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Strong relationships between joint- diagonalization and tensor decompositions have been established recently. In this paper we propose a finite impulse response (FIR) channel identification method based on the Parafac decomposition of a 3rd-order tensor composed of the 4-th order output cumulants. By avoiding the prewhitening operation required by joint-diagonalization based methods, our method is shown to improve the estimation performance provided by the classic joint-diagonalization algorithm.\",\"PeriodicalId\":271294,\"journal\":{\"name\":\"2006 International Telecommunications Symposium\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Telecommunications Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITS.2006.4433376\",\"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 International Telecommunications Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITS.2006.4433376","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parafac-based blind channel identification using 4th-order cumulants
Strong relationships between joint- diagonalization and tensor decompositions have been established recently. In this paper we propose a finite impulse response (FIR) channel identification method based on the Parafac decomposition of a 3rd-order tensor composed of the 4-th order output cumulants. By avoiding the prewhitening operation required by joint-diagonalization based methods, our method is shown to improve the estimation performance provided by the classic joint-diagonalization algorithm.