Multi-reference Adaptive Gain FXLMS Algorithm for Active Noise Control

Multi-reference least mean square algorithm (MR-FXLMS) has been performed more efficiently than the traditional Least mean square algorithm (FXLMS). In this paper, a multi-reference adaptive gain (MRAG-FXLMS) algorithm which is designed to enhance the performance of the multi-reference FXLMS algorithm. The proposed method is derived by combining a novel multi-reference structure and adaptive gain. The adaptive gain is obtained by using the gradient descent method. To evaluate the effectiveness of the proposed algorithm, a computational complexity analysis is conducted. According to the simulation results, it can be concluded that the proposed MRAG-FXLMS algorithm achieves excellent performance in convergence rate and steady-state error compared with the conventional FXLMS algorithm and MR-FXLMS algorithm.
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