{"title":"一种新的归一化有符号回归LMS算法","authors":"K. Takahashi, S. Mori","doi":"10.1109/ICCS.1992.255075","DOIUrl":null,"url":null,"abstract":"The normalized signed regressor algorithm is the NLMS algorithm based on clipping of the input samples which are elements of the input data vector. In the new algorithm, a clipped sample is used to update coefficients when the absolute value of the sample is larger than the average of the absolute values of the input samples. Analysis shows that the proposed algorithm has better convergence characteristics than the conventional normalized signed regressor algorithm.<<ETX>>","PeriodicalId":223769,"journal":{"name":"[Proceedings] Singapore ICCS/ISITA `92","volume":"17 8","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A new normalized signed regressor LMS algorithm\",\"authors\":\"K. Takahashi, S. Mori\",\"doi\":\"10.1109/ICCS.1992.255075\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The normalized signed regressor algorithm is the NLMS algorithm based on clipping of the input samples which are elements of the input data vector. In the new algorithm, a clipped sample is used to update coefficients when the absolute value of the sample is larger than the average of the absolute values of the input samples. Analysis shows that the proposed algorithm has better convergence characteristics than the conventional normalized signed regressor algorithm.<<ETX>>\",\"PeriodicalId\":223769,\"journal\":{\"name\":\"[Proceedings] Singapore ICCS/ISITA `92\",\"volume\":\"17 8\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings] Singapore ICCS/ISITA `92\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCS.1992.255075\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] Singapore ICCS/ISITA `92","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCS.1992.255075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The normalized signed regressor algorithm is the NLMS algorithm based on clipping of the input samples which are elements of the input data vector. In the new algorithm, a clipped sample is used to update coefficients when the absolute value of the sample is larger than the average of the absolute values of the input samples. Analysis shows that the proposed algorithm has better convergence characteristics than the conventional normalized signed regressor algorithm.<>
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