the variable step-size wavelet transform-domain lms adaptive filter algorithm

In this paper, the wavelet transform domain least mean squares (wtdlms) adaptive algorithm with variablestep-size (vss) is established. the step-size changes according to the largest decrease in mean square deviation. to keep the 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 faster convergence rate and lower misadjustment than conventional wtdlms. the theoretical relations are also verified by presenting various experimental results.