An improved algorithm based on noise estimation
Qiang Li, Qiu-ju Zheng · 2013
In order to improve the accuracy of noise estimation in the non-stationary environment, this paper proposes a new improved noise estimation algorithm. The minimum searching is depended on a fixed length of time window instead of fixed window, compare with the traditional algorithm, this algorithm can improve the tracking delay. The smoothing parameter can be calculated through constraining the variance. Simulation results show that this algorithm possesses a more short delay in tracking the behavior of the background noise, and it has a lower mean square error of noise estimation. Smoothing parameter can be calculated through constraining the variance. Simulation results show that this algorithm possesses a more short delay in tracking the behavior of the background noise, and it has a lower mean square error of noise estimation.