Mean square error analysis for the fast LMS-sine algorithm

An analysis is made of the mean square error for the fast least mean square (LMS)-sine algorithm. It is shown that during the very early stages of adaptation the mean square error increases to accommodate the transients which take place in the weight updates. At steady state, the mean square error obtained is much less than that for the classical LMS algorithm due to a reduction in the misadjustment error. It is also shown through simulations that the behavior of the error is as anticipated by the analytical results.<<ETX>>