{"title":"基于恒模误差准则的三种盲均衡算法的比较","authors":"Tracie A. Schirtzinger, Xiaohui Li, W. Jenkins","doi":"10.1109/ICASSP.1995.480414","DOIUrl":null,"url":null,"abstract":"Three constant modulus algorithms (CMA), the fast quasi-Newton CMA, the transform domain CMA, and the genetic search based CMA are proposed in this paper. The performances of these three algorithms are compared with each other via computer simulation. It is shown that the fast quasi-Newton CMA and the transform domain CMA achieve much faster convergence rate than the constant modulus algorithm based on the LMS algorithm. This fact shows that the whitening technique is not only useful but also necessary for the CMA.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"45 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"A comparison of three algorithms for blind equalization based on the constant modulus error criterion\",\"authors\":\"Tracie A. Schirtzinger, Xiaohui Li, W. Jenkins\",\"doi\":\"10.1109/ICASSP.1995.480414\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Three constant modulus algorithms (CMA), the fast quasi-Newton CMA, the transform domain CMA, and the genetic search based CMA are proposed in this paper. The performances of these three algorithms are compared with each other via computer simulation. It is shown that the fast quasi-Newton CMA and the transform domain CMA achieve much faster convergence rate than the constant modulus algorithm based on the LMS algorithm. This fact shows that the whitening technique is not only useful but also necessary for the CMA.\",\"PeriodicalId\":300119,\"journal\":{\"name\":\"1995 International Conference on Acoustics, Speech, and Signal Processing\",\"volume\":\"45 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1995 International Conference on Acoustics, Speech, and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.1995.480414\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1995 International Conference on Acoustics, Speech, and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.1995.480414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A comparison of three algorithms for blind equalization based on the constant modulus error criterion
Three constant modulus algorithms (CMA), the fast quasi-Newton CMA, the transform domain CMA, and the genetic search based CMA are proposed in this paper. The performances of these three algorithms are compared with each other via computer simulation. It is shown that the fast quasi-Newton CMA and the transform domain CMA achieve much faster convergence rate than the constant modulus algorithm based on the LMS algorithm. This fact shows that the whitening technique is not only useful but also necessary for the CMA.