{"title":"基于二阶统计量的信号分离方法的统计分析","authors":"T. Gustafsson, U. Lindgren, H. Sahlin","doi":"10.1109/ICASSP.2000.861858","DOIUrl":null,"url":null,"abstract":"This paper explores an existing method for signal separation, which is based on second order statistics. Here, statistical analysis of a generalized version of the original algorithm is given. The generalized method includes a weighting matrix, and a result of the statistical analysis is that the best possible weighting is found. The problem of initialization of the involved non-linear optimization is also discussed.","PeriodicalId":164817,"journal":{"name":"2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Statistical analysis of a signal separation method based on second order statistics\",\"authors\":\"T. Gustafsson, U. Lindgren, H. Sahlin\",\"doi\":\"10.1109/ICASSP.2000.861858\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper explores an existing method for signal separation, which is based on second order statistics. Here, statistical analysis of a generalized version of the original algorithm is given. The generalized method includes a weighting matrix, and a result of the statistical analysis is that the best possible weighting is found. The problem of initialization of the involved non-linear optimization is also discussed.\",\"PeriodicalId\":164817,\"journal\":{\"name\":\"2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.2000.861858\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2000.861858","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical analysis of a signal separation method based on second order statistics
This paper explores an existing method for signal separation, which is based on second order statistics. Here, statistical analysis of a generalized version of the original algorithm is given. The generalized method includes a weighting matrix, and a result of the statistical analysis is that the best possible weighting is found. The problem of initialization of the involved non-linear optimization is also discussed.
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