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-NLAIS) 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 relaxes such trade-off. Both analysis and simulation results show that the proposed VSS-NLMS algorithm outperforms the FSS-NLMS algorithm.