Convergence and Steady-State Analysis of a Variable Step-Size Normalized LMS Algorithm

摘要

This paper presents a simple and robust variable step-size Normalized LMS (VSS-NLMS) adaptive algorithm. The fixed step-size NLMS algorithm (FSS-NLMS) usually results in a trade-off between the residual error and the convergence speed of the algorithm. The variable step-size NLMS algorithm presented here will relax such trade-off. Both analysis and simulation results show that the proposed VSS-NLMS algorithm outperforms the FSS-NLMS algorithm.