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arXiv · 2208.08856

Study of General Robust Subband Adaptive Filtering

Yi Yu·Hongsen He·Rodrigo C. de Lamare·Badong Chen
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Abstract

In this paper, we propose a general robust subband adaptive filtering (GR-SAF) scheme against impulsive noise by minimizing the mean square deviation under the random-walk model with individual weight uncertainty. Specifically, by choosing different scaling factors such as from the M-estimate and maximum correntropy robust criteria in the GR-SAF scheme, we can easily obtain different GR-SAF algorithms. Importantly, the proposed GR-SAF algorithm can be reduced to a variable regularization robust normalized SAF algorithm, thus having fast convergence rate and low steady-state error. Simulations in the contexts of system identification with impulsive noise and echo cancellation with double-talk have verified that the proposed GR-SAF algorithms outperforms its counterparts.

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Yi Yu, Hongsen He, Rodrigo C. de Lamare, Badong Chen. 2022-08-04. Study of General Robust Subband Adaptive Filtering. https://arxiv.org/abs/2208.08856

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