{"title":"Theoretic analysis of the /spl gamma/-LMS algorithm","authors":"Wen-Rong Wu, Po-Cheng Chen","doi":"10.1109/APCCAS.1994.514580","DOIUrl":null,"url":null,"abstract":"The AR modeling is widely used in signal processing. The coefficients of AR model can be easily obtained by a LMS prediction error filter. However, it is known that such filter will give bias coefficients when the input signal is corrupted by noise. In previous works, Treicher [1979] suggested the /spl gamma/-LMS algorithm to reduce the bias problem caused by Gaussian noise. This paper gives the theoretical analysis of the /spl gamma/-LMS algorithm. We derive the close form solution of the second order statistics of the tap-weight vector. Computer simulations are provided to show the accuracy of our theoretical result.","PeriodicalId":231368,"journal":{"name":"Proceedings of APCCAS'94 - 1994 Asia Pacific Conference on Circuits and Systems","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of APCCAS'94 - 1994 Asia Pacific Conference on Circuits and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCCAS.1994.514580","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The AR modeling is widely used in signal processing. The coefficients of AR model can be easily obtained by a LMS prediction error filter. However, it is known that such filter will give bias coefficients when the input signal is corrupted by noise. In previous works, Treicher [1979] suggested the /spl gamma/-LMS algorithm to reduce the bias problem caused by Gaussian noise. This paper gives the theoretical analysis of the /spl gamma/-LMS algorithm. We derive the close form solution of the second order statistics of the tap-weight vector. Computer simulations are provided to show the accuracy of our theoretical result.
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