Statistics Behavior of Individual-Weighting-Factors SSAF Algorithm Under Errors-in-Variables Model

The individual-weighting-factors sign subband adaptive filtering (IWF-SSAF) algorithm has acquired attention due to its quick convergence and brilliant robustness against impulsive interference. However, its statistics behavior has not been investigated under errors-in-variables (EIV) model, which system input and output are all corrupted by noise. Therefore, in this letter, the statistics analysis including transient and steady-state behaviors of IWF-SSAF is derived in mean and mean-square senses by virtue of some frequently-utilized assumptions and Price's theorem. Finally, numerical simulations under system identification scenario manifest that the simulated and theoretical results are in good agreement in different environments, which corroborate the accurateness of the derived theoretical models.