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A bias-compensated normalized subband adaptive filter (BC-NSAF) algorithm is proposed for system identification. In the proposed algorithm, a bias-compensation vector is derived to eliminate the bias caused by the noisy input signals. To estimate the input noise variance, a new estimation method is proposed, which does not require the input-output variance ratio in advance. Simulation results show that the proposed algorithm obtains better convergence performance than the existing algorithms in the presence of noisy input signals.
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Zheng et al. (2016) studied this question.
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