Acoustic Noise Cancellation based on a Novel Adaptive Algorithm

The least mean square (LMS) adaptive algorithm is widely used in acoustic noise cancellation (ANC) scenario. In this scenario, speech signals usually have high amplitude and sudden variations that are modeled by impulsive disturbances and it is wellknown that the acoustic channels usually have been sparse impulse response. Impulsive noise and sparsity of the acoustic channel are two important challenges in the ANC scenario that have paid special attention, recently. This paper presents a novel adaptive noise cancellation algorithm, to address the poor performance of the LMS algorithm in presence of impulsive noise along with a sparse impulse response. In order to eliminate impulsive noise from speech signal, the information theoretic criterion is used in the proposed cost function andthe zero norm is also employed to deal with the sparsity feature of the acoustic channel impulse response. Simulation results indicates the superiority of the proposed algorithm in presence of impulsive noise along with sparsity condition of acoustic channel.