{"title":"一种用于跟踪离散时间fBm过程的新颖最小均方算法","authors":"A. Gupta, S. Joshi","doi":"10.1109/INDCON.2006.302790","DOIUrl":null,"url":null,"abstract":"This paper presents a novel variable step-size LMS (VSLMS) algorithm for tracking a discrete-time fractional Brownian motion that is inherently non-stationary. In the proposed work, one of the step-size values requires time-varying constraints for the algorithm to converge to the optimal weights whereas the constraints on the remaining step-size values are time-invariant in the decoupled weight vector space. It computes the step-size matrix by estimating the Hurst exponent required to characterize the statistical properties of the signal at the input of the adaptive filter. The experimental set-up of an adaptive channel equalizer is considered for equalization of these signals transmitted over stationary AWGN channel. The performance of the proposed variable step-size LMS algorithm is compared with the unsigned VSLMS algorithm and is observed to be better for the class of non-stationary signals considered","PeriodicalId":122715,"journal":{"name":"2006 Annual IEEE India Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Novel Least Mean Squares Algorithm for tracking a Discrete-time fBm Process\",\"authors\":\"A. Gupta, S. Joshi\",\"doi\":\"10.1109/INDCON.2006.302790\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a novel variable step-size LMS (VSLMS) algorithm for tracking a discrete-time fractional Brownian motion that is inherently non-stationary. In the proposed work, one of the step-size values requires time-varying constraints for the algorithm to converge to the optimal weights whereas the constraints on the remaining step-size values are time-invariant in the decoupled weight vector space. It computes the step-size matrix by estimating the Hurst exponent required to characterize the statistical properties of the signal at the input of the adaptive filter. The experimental set-up of an adaptive channel equalizer is considered for equalization of these signals transmitted over stationary AWGN channel. The performance of the proposed variable step-size LMS algorithm is compared with the unsigned VSLMS algorithm and is observed to be better for the class of non-stationary signals considered\",\"PeriodicalId\":122715,\"journal\":{\"name\":\"2006 Annual IEEE India Conference\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 Annual IEEE India Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INDCON.2006.302790\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 Annual IEEE India Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDCON.2006.302790","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Least Mean Squares Algorithm for tracking a Discrete-time fBm Process
This paper presents a novel variable step-size LMS (VSLMS) algorithm for tracking a discrete-time fractional Brownian motion that is inherently non-stationary. In the proposed work, one of the step-size values requires time-varying constraints for the algorithm to converge to the optimal weights whereas the constraints on the remaining step-size values are time-invariant in the decoupled weight vector space. It computes the step-size matrix by estimating the Hurst exponent required to characterize the statistical properties of the signal at the input of the adaptive filter. The experimental set-up of an adaptive channel equalizer is considered for equalization of these signals transmitted over stationary AWGN channel. The performance of the proposed variable step-size LMS algorithm is compared with the unsigned VSLMS algorithm and is observed to be better for the class of non-stationary signals considered