{"title":"频域Volterra滤波器的归一化块LMS算法","authors":"S. Im","doi":"10.1109/HOST.1997.613506","DOIUrl":null,"url":null,"abstract":"The objective of the paper is to introduce a new adaptive filtering algorithm for estimating frequency-domain second-order Volterra filter coefficients. The approach rests upon the normalized LMS (NLMS) algorithm and the frequency-domain block LMS algorithm. The utilization of the normalized LMS algorithm facilitates choice of a proper step size, with which the adaptive frequency domain Volterra filter is guaranteed to be convergent in the mean-squared sense, and improves convergence rate. The frequency-domain block LMS algorithm estimates frequency-domain second-order Volterra filter coefficients which correspond to the DFT of the time-domain Volterra filter coefficients.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"252 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A normalized block LMS algorithm for frequency-domain Volterra filters\",\"authors\":\"S. Im\",\"doi\":\"10.1109/HOST.1997.613506\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of the paper is to introduce a new adaptive filtering algorithm for estimating frequency-domain second-order Volterra filter coefficients. The approach rests upon the normalized LMS (NLMS) algorithm and the frequency-domain block LMS algorithm. The utilization of the normalized LMS algorithm facilitates choice of a proper step size, with which the adaptive frequency domain Volterra filter is guaranteed to be convergent in the mean-squared sense, and improves convergence rate. The frequency-domain block LMS algorithm estimates frequency-domain second-order Volterra filter coefficients which correspond to the DFT of the time-domain Volterra filter coefficients.\",\"PeriodicalId\":305928,\"journal\":{\"name\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"volume\":\"252 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HOST.1997.613506\",\"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 of the IEEE Signal Processing Workshop on Higher-Order Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HOST.1997.613506","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A normalized block LMS algorithm for frequency-domain Volterra filters
The objective of the paper is to introduce a new adaptive filtering algorithm for estimating frequency-domain second-order Volterra filter coefficients. The approach rests upon the normalized LMS (NLMS) algorithm and the frequency-domain block LMS algorithm. The utilization of the normalized LMS algorithm facilitates choice of a proper step size, with which the adaptive frequency domain Volterra filter is guaranteed to be convergent in the mean-squared sense, and improves convergence rate. The frequency-domain block LMS algorithm estimates frequency-domain second-order Volterra filter coefficients which correspond to the DFT of the time-domain Volterra filter coefficients.
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