A variable step-size LMS adaptive filtering algorithm for speech denoising in VoIP

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.