The variable step-size wavelet transform-domain LMS adaptive filter algorithm

In this paper, the Wavelet Transform-Domain Least-Mean-Squares (WT-DLMSs) adaptive algorithm with Variable Step-Size (VSS) is established. The step-size changes according to the largest decrease of mean square deviation. To keep computational complexity low, the Haar Wavelet Transform (HWT) is utilized as a transform. In addition, the mean square performance analysis of the VSS-WTDLMS is studied in the stationary and nonstationary environments, and the theoretical relations for transient and steady-state performances are established. The simulation results show that the proposed VSS-WTDLMS has a faster convergence rate and lower maladjustment, compared to conventional WTDLMS. The theoretical relations are verified by presenting various experimental results. (C) 2020 Sharif University of Technology. All rights reserved.