M-estimate based normalized subband adaptive filter algorithm: Performance analysis and improvements

This article studies the mean and mean-square behaviors of the M-estimate based normalized subband adaptive filter algorithm (M-NSAF) with robustness against impulsive noise. Based on the contaminated-Gaussian noise model, the stability condition, transient and steady-state results of the algorithm are formulated analytically. These analysis results help us to better understand the M-NSAF performance in impulsive noise. To further obtain fast convergence and low steady-state estimation error, we derive a variable step size (VSS) M-NSAF algorithm. This VSS scheme is also generalized to the proportionate M-NSAF variant for sparse systems. Computer simulations on the system identification in impulsive noise and the acoustic echo cancellation with double-talk are performed to demonstrate our theoretical analysis and the effectiveness of the proposed algorithms.

Acoustic echo cancellation, M-estimate, impulsive noise, subband adaptive filter, variable step size

10.1109/TASLP.2019.2950597

1558-7916

225-239

Yu, Yi

ccad4322-548f-4911-a135-2c845712abd3

He, Hongsen

09e5276d-3d5e-4f23-8c08-e502573e5165

Chen, Badong

3c4b8c94-4247-43f0-9b97-229c6cf460d2

Li, Jianghui

9c589194-00fa-4d42-abaf-53a32789cc5e

Zhang, Youwen

7aa2372a-67e3-4f9e-8acb-22e604c34fd5

Lu, Lu

ae7aeabd-2f50-4412-b778-141a5cd9861b

2020

Yu, Yi

ccad4322-548f-4911-a135-2c845712abd3

He, Hongsen

09e5276d-3d5e-4f23-8c08-e502573e5165

Chen, Badong

3c4b8c94-4247-43f0-9b97-229c6cf460d2

Li, Jianghui

9c589194-00fa-4d42-abaf-53a32789cc5e

Zhang, Youwen

7aa2372a-67e3-4f9e-8acb-22e604c34fd5

Lu, Lu

ae7aeabd-2f50-4412-b778-141a5cd9861b

Yu, Yi, He, Hongsen, Chen, Badong, Li, Jianghui, Zhang, Youwen and Lu, Lu (2020) M-estimate based normalized subband adaptive filter algorithm: Performance analysis and improvements. IEEE Transactions on Audio, Speech and Language Processing, 28, 225-239, [8888205]. (doi:10.1109/TASLP.2019.2950597).

Record type: Article

Abstract

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MNSAF_accepted - Accepted Manuscript

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Accepted/In Press date: 25 October 2019

e-pub ahead of print date: 31 October 2019

Published date: 2020

Additional Information: Funding Information: Manuscript received May 14, 2019; revised September 25, 2019 and October 21, 2019; accepted October 25, 2019. Date of publication October 31, 2019; date of current version December 24, 2019. This work was supported in part by the National Science Foundation of China (NSFC) under Grants 61901400, 61771411, and 61901285, and in part by the Doctoral Research Fund of the Southwest University of Science and Technology in China (No. 19zx7122). The work of H. He was supported in part by the NSFC under Grant 61571376, in part by the NSFC key program under Grant 61831019, and in part by the NSFCISF joint research program under Grant 61761146001. The work of J. Li was supported by the European Unions Horizon 2020 research and innovation programme under the Grant 654462 (STEMM-CCS). The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Stefania Cecchi. (Corresponding authors: Hongsen He; Yi Yu.) Y. Yu and H. He are with the School of Information Engineering, Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Southwest University of Science and Technology, Mianyang 621010, China (e-mail: yuyi_xyuan@163.com; hongsenhe@gmail.com). Publisher Copyright: © 2014 IEEE.

Keywords: Acoustic echo cancellation, M-estimate, impulsive noise, subband adaptive filter, variable step size