BIAS REMOVAL IN EQUATION ERROR ADAPTIVE IIR FILTERS

In the equation-error formulation of adaptive IIR filters, the estimat ed parameters contain bias when there is noise in the desired response . A method that can eliminate this bias is investigated. The idea is t o maintain a quadratic constraint on the feedback coefficients so that the noise contributes only a constant term to the mean-square error. This term does not affect minimization and thus the bias is eliminated . A quadratically constrained stochastic gradient search method is app lied for optimization and convergence behavior, when the noise is whit e, is analyzed. Adaptation of the feedback FIR filter in second-order cascade form, useful for stability monitoring, is also considered. Whe n the noise is nonwhite, the technique requires an adaptive whitening filter. Simulation results are included to demonstrate the bias remova l capability of the method, corroborate the theoretical developments, and compare with existing techniques.