A New Efficient Multi-Channel Fast NLMS (MC-FNLMS) Adaptive Algorithm for Audio Teleconferencing systems

-In this paper, we propose a new multichannel fast normalized least mean square (MC-FNLMS) algorithm for audio teleconferencing systems. The main idea behind the proposed MC-FNLMS algorithm is based on the introduction of a first order prediction process on the input noisy signals before the adaptive filtering process of each channel. The proposed algorithm is considered as an alternative solution for the existing algorithm in multi-channel applications. A full stability analysis of the proposed algorithm is derived along this paper. Simulation results of a comparison between the proposed MC-FNLMS algorithm and the two classical Multichannel Normalized Least Mean Square (MC-NLMS) and the Multichannel Affine Projection (MC-APA) algorithms, in terms of convergence speed, noise reduction and computational complexity, show the superiority of the proposed algorithm on multichannel adaptive noise reduction.

Automated summary

This paper proposes a new multichannel fast normalized least mean square (MC-FNLMS) algorithm for audio teleconferencing systems. The algorithm improves multichannel adaptive noise reduction by introducing a first order prediction process on the input signals. Compared with existing algorithms, the proposed algorithm demonstrates faster convergence speed, better noise reduction performance, and lower computational complexity.