{"title":"一种有效的复杂源盲分离技术","authors":"J. Cardoso, A. Souloumiac","doi":"10.1109/HOST.1993.264552","DOIUrl":null,"url":null,"abstract":"Blind identification of spatial mixtures allows an array of sensors to implement source separation when the array manifold is unknown. A family of 4th-order cumulant-based criteria for blind source separation is introduced. These criteria involve a set of cumulant matrices whose joint diagonalization is equivalent to criterion optimization. An efficient algorithm is described to this effect. Simulations on both real and synthetic signals are provided.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"78","resultStr":"{\"title\":\"An efficient technique for the blind separation of complex sources\",\"authors\":\"J. Cardoso, A. Souloumiac\",\"doi\":\"10.1109/HOST.1993.264552\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Blind identification of spatial mixtures allows an array of sensors to implement source separation when the array manifold is unknown. A family of 4th-order cumulant-based criteria for blind source separation is introduced. These criteria involve a set of cumulant matrices whose joint diagonalization is equivalent to criterion optimization. An efficient algorithm is described to this effect. Simulations on both real and synthetic signals are provided.<<ETX>>\",\"PeriodicalId\":439030,\"journal\":{\"name\":\"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"78\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HOST.1993.264552\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HOST.1993.264552","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An efficient technique for the blind separation of complex sources
Blind identification of spatial mixtures allows an array of sensors to implement source separation when the array manifold is unknown. A family of 4th-order cumulant-based criteria for blind source separation is introduced. These criteria involve a set of cumulant matrices whose joint diagonalization is equivalent to criterion optimization. An efficient algorithm is described to this effect. Simulations on both real and synthetic signals are provided.<>