{"title":"基于阵列平均分数阶傅里叶变换的盲源分离","authors":"Lu-ping Zhou, Bingrong Li, Chun-feng Wang","doi":"10.1109/CCDC.2009.5194850","DOIUrl":null,"url":null,"abstract":"In this paper, a novel blind source separation method based on the array-averaged Fractional Fourier Transform is proposed. This method can decrease the noise levels, and suppress the interactions of the source signals, which lead to better separation performance. Compared with the previous blind source separation techniques based on the time-frequency distributions, this proposed method produces little crossterms, and it does not require whitening, joint-diagonalization, and bilinear signal synthesis. The improved efficiency of the method is verified by the simulation.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"259 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Blind source separation based on the array-averaged Fractional Fourier Transform\",\"authors\":\"Lu-ping Zhou, Bingrong Li, Chun-feng Wang\",\"doi\":\"10.1109/CCDC.2009.5194850\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a novel blind source separation method based on the array-averaged Fractional Fourier Transform is proposed. This method can decrease the noise levels, and suppress the interactions of the source signals, which lead to better separation performance. Compared with the previous blind source separation techniques based on the time-frequency distributions, this proposed method produces little crossterms, and it does not require whitening, joint-diagonalization, and bilinear signal synthesis. The improved efficiency of the method is verified by the simulation.\",\"PeriodicalId\":127110,\"journal\":{\"name\":\"2009 Chinese Control and Decision Conference\",\"volume\":\"259 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Chinese Control and Decision Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2009.5194850\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Chinese Control and Decision Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2009.5194850","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Blind source separation based on the array-averaged Fractional Fourier Transform
In this paper, a novel blind source separation method based on the array-averaged Fractional Fourier Transform is proposed. This method can decrease the noise levels, and suppress the interactions of the source signals, which lead to better separation performance. Compared with the previous blind source separation techniques based on the time-frequency distributions, this proposed method produces little crossterms, and it does not require whitening, joint-diagonalization, and bilinear signal synthesis. The improved efficiency of the method is verified by the simulation.