Mean weight behavior of the filtered-X LMS algorithm

A new stochastic analysis is presented for the filtered-X LMS (FXLMS) algor ithm. The analysis does not use independence theory, An analytical model is derived for the mean behavior of the adaptive weights, The model is valid for white or colored reference inputs and accurately predicts the mean weig ht behavior even for large step sizes, The constrained Wiener solution is d etermined as a function of the input statistics and the impulse responses o f the adaptation loop filters, Effects of secondary path estimation errors are studied. Monte Carlo simulations demonstrate the accuracy of the theore tical model.