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A New Variable Step-Size NLMS Algorithm and Its Performance Analysis

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2 Author(s)
Hsu-Chang Huang ; Dept. of Electr. Eng., Yuan-Ze Univ., Chungli, Taiwan ; Junghsi Lee

Numerous variable step-size normalized least mean-square (VSS-NLMS) algorithms have been derived to solve the dilemma of fast convergence rate or low excess mean-square error in the past two decades. This paper proposes a new, easy to implement, nonparametric VSS-NLMS algorithm that employs the mean-square error and the estimated system noise power to control the step-size update. Theoretical analysis of its steady-state behavior shows that, when the input is zero-mean Gaussian distributed, the misadjustment depends only on a parameter β controlling the update of step size. Simulation experiments show that the proposed algorithm performs very well. Furthermore, the theoretical steady-state behavior is in very good agreement with the experimental results.

Published in:

IEEE Transactions on Signal Processing  (Volume:60 ,  Issue: 4 )