ADAPTIVE FILTER UPDATE NORMALIZATION

摘要

Loop gain normalization is employed in adaptive filters to control weighting of the filter characteristic updates in order to converge properly to a desired filter characteristic. Filter stability and rapid high quality convergence is realized for a variety of received or inputted signals by employing both long term and fast attack estimates of a prescribed input signal characteristic to normalize the update gain. In one embodiment, both long term and fast attack input signal power estimates are generated and one of the two estimate values is selected to normalize the update gain. Specifically, the fast attack estimate is modified by a predetermined value and, then, the larger of the long term estimate and modified fast attack estimate is selected to normalize the update gain.