Steady-state error in adaptive mean-square minimization

This paper considers the steady-state mean-square error when an adaptive linear estimator is used on a stationary time series. The estimator weights are adjusted periodically by moving a small increment in the direction of the estimated gradient. Under very general conditions the asymptotic mean-square error is bounded and under more restrictive conditions is evaluated exactly.