Adaptive Variable Step-Size Algorithm for Acoustic Noise Cancellation by using Multiple Sub-Filters Approach

Abstract

paper, a novel algorithm for cancelling noise from the speech signal in real time environment is proposed. Least Mean Square (LMS) adaptive noise cancellers are often used to recover signal corrupted by additive noise due to its simplicity in implementation. But it has limitation when the desired signal is strong, that the excess mean-square errors increase linearly with the desired signal power. This results in downgraded performance when the desired signal exhibits large power fluctuations. In the proposed algorithm we use the benefits of both variable step size (VSS) LMS algorithm and Normalized Differential LMS (NDLMS) algorithm to deal with this situation. One more addition of this algorithm is that it uses the concept of decomposing the long adaptive filter into low order multiple sub-filters to relieve the effect of slow convergence of that long adaptive filter. Finally, The proposed (P-VSSNDLMS) algorithm yields faster convergence with minimum mean square error in simulations which carried out using real speech signal with different noise power levels. KeywordsNoise canceller (ANC), mean square error (MSE), VSSNDLMS, multiple sub-filters.