{"title":"盲源分离的步长优化EASI算法","authors":"Weihong Fu, Xiaoniu Yang, Naian Liu","doi":"10.1109/CIS.2007.15","DOIUrl":null,"url":null,"abstract":"Aiming at the problem of blind source separation of the communication signals, we propose a step size optimization equivariant adaptive source separation via independence (SO-EASI) algorithm basing on the EASI block based algorithm. This algorithm adjusts the step-size by the steepest descent method and thereby greatly increases its convergence speed whatever value the step-size is initialized. Simulation results show that SO-EASI algorithm can effectively blindly separate the communication signals and these results also support the expected improvement in convergence speed of the approach.","PeriodicalId":127238,"journal":{"name":"2007 International Conference on Computational Intelligence and Security (CIS 2007)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Step-Size Optimization EASI Algorithm for Blind Source Separation\",\"authors\":\"Weihong Fu, Xiaoniu Yang, Naian Liu\",\"doi\":\"10.1109/CIS.2007.15\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the problem of blind source separation of the communication signals, we propose a step size optimization equivariant adaptive source separation via independence (SO-EASI) algorithm basing on the EASI block based algorithm. This algorithm adjusts the step-size by the steepest descent method and thereby greatly increases its convergence speed whatever value the step-size is initialized. Simulation results show that SO-EASI algorithm can effectively blindly separate the communication signals and these results also support the expected improvement in convergence speed of the approach.\",\"PeriodicalId\":127238,\"journal\":{\"name\":\"2007 International Conference on Computational Intelligence and Security (CIS 2007)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Computational Intelligence and Security (CIS 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS.2007.15\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Computational Intelligence and Security (CIS 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2007.15","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Step-Size Optimization EASI Algorithm for Blind Source Separation
Aiming at the problem of blind source separation of the communication signals, we propose a step size optimization equivariant adaptive source separation via independence (SO-EASI) algorithm basing on the EASI block based algorithm. This algorithm adjusts the step-size by the steepest descent method and thereby greatly increases its convergence speed whatever value the step-size is initialized. Simulation results show that SO-EASI algorithm can effectively blindly separate the communication signals and these results also support the expected improvement in convergence speed of the approach.