A variable step-size LMS adaptive filtering algorithm for speech denoising in VoIP
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DOI: 10.23977/iccsc.2017.1010
Corresponding Author
Hongyu Chen
ABSTRACT
There is a contradiction between convergence speed and steady-state error in the
LMS algorithm. When the step size factor is too large, the convergence speed is fast, but the
error is larger. Otherwise, the reverse. In view of this contradiction, based on the original
LMS algorithm, consider from the correlation of the signal itself, has proposed a variable
step size LMS algorithm based on DCT transform. This algorithm combined with the
original DCT-LMS algorithm, through the introduction of Lorentzian function to achieve the
change of step size factor, take full advantage of the relevant capacity of the DCT transform
and Lorentzian function of the fast convergence ability. Simulation results show that the
proposed algorithm has better convergence performance than the traditional adaptive
filtering algorithm and DCT-LMS algorithm, and has better steady state error.
KEYWORDS
Adaptive filtering, Lorentzian function, DCT transform, LMS algorithm.