LAUSR

To thoroughly exploit the decorrelation property of the traditional sign subband adaptive filter (SSAF), an individual weighting factors SSAF (IWF-SSAF) was presented. However, when the input of the adaptive filter is polluted by white Gaussian noise, the IWF-SSAF will produce estimation bias for unknown system identification. Thus, this brief proposes the bias-compensated IWF-SSAF (BC-IWF-SSAF) for resolving the above trouble. Especially, the unbiased criterion is applied to obtain compensation term for the conventional IWF-SSAF to alleviate the effect of noisy input. The proposed BC-IWF-SSAF both retains stability of impulse noise and decreases the estimated bias. The stable condition of the proposed BC-IWF-SSAF is achieved resorting to Price’s theorem with some reasonable assumptions and theorems. In addition, the complexity is given as well. Finally, simulations confirm the superiority of the proposed BC-IWF-SSAF algorithm.