The Wavelet Transform-Domain LMS Adaptive Filter Algorithm with Variable Step-Size
نویسندگان
چکیده مقاله:
The wavelet transform-domain least-mean square (WTDLMS) algorithm uses the self-orthogonalizing technique to improve the convergence performance of LMS. In WTDLMS algorithm, the trade-off between the steady-state error and the convergence rate is obtained by the fixed step-size. In this paper, the WTDLMS adaptive algorithm with variable step-size (VSS) is established. The step-size in each subfilter changes according to the largest decrease in mean square deviation. The simulation results show that the proposed VSS-WTDLMS has faster convergence rate and lower misadjustment than ordinary WTDLMS.
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عنوان ژورنال
دوره 13 شماره 3
صفحات 213- 218
تاریخ انتشار 2017-09
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