Rafael Assato Ando, Leonardo Tomazeli Duarte, R. Attux
{"title":"带限信号过定线性二次混合的盲源分离","authors":"Rafael Assato Ando, Leonardo Tomazeli Duarte, R. Attux","doi":"10.1109/ITS.2014.6947974","DOIUrl":null,"url":null,"abstract":"In this paper, we address the problem of blind source separation for linear quadratic mixtures. The proposed approach relies on the assumption that the input signals are band-limited. As the nonlinearity of the mixing process tends to widen the spectra of the mixture signals, and taking into account the fact that there are more mixtures than sources in the overdetermined version of the problem, we propose a method that uses the additional mixtures to eliminate the nonlinearities of the observed signals. This gives rise to a linear problem that can be solved with standard methods previously analyzed in the literature. Numerical experiments show that the proposed algorithm successfully separates the sources under the proposed conditions.","PeriodicalId":359348,"journal":{"name":"2014 International Telecommunications Symposium (ITS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Blind source separation for overdetermined linear quadratic mixtures of bandlimited signals\",\"authors\":\"Rafael Assato Ando, Leonardo Tomazeli Duarte, R. Attux\",\"doi\":\"10.1109/ITS.2014.6947974\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we address the problem of blind source separation for linear quadratic mixtures. The proposed approach relies on the assumption that the input signals are band-limited. As the nonlinearity of the mixing process tends to widen the spectra of the mixture signals, and taking into account the fact that there are more mixtures than sources in the overdetermined version of the problem, we propose a method that uses the additional mixtures to eliminate the nonlinearities of the observed signals. This gives rise to a linear problem that can be solved with standard methods previously analyzed in the literature. Numerical experiments show that the proposed algorithm successfully separates the sources under the proposed conditions.\",\"PeriodicalId\":359348,\"journal\":{\"name\":\"2014 International Telecommunications Symposium (ITS)\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Telecommunications Symposium (ITS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITS.2014.6947974\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Telecommunications Symposium (ITS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITS.2014.6947974","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Blind source separation for overdetermined linear quadratic mixtures of bandlimited signals
In this paper, we address the problem of blind source separation for linear quadratic mixtures. The proposed approach relies on the assumption that the input signals are band-limited. As the nonlinearity of the mixing process tends to widen the spectra of the mixture signals, and taking into account the fact that there are more mixtures than sources in the overdetermined version of the problem, we propose a method that uses the additional mixtures to eliminate the nonlinearities of the observed signals. This gives rise to a linear problem that can be solved with standard methods previously analyzed in the literature. Numerical experiments show that the proposed algorithm successfully separates the sources under the proposed conditions.