Determination the range that contain the best learning parameter to estimate AR models by using adaptation

Abstract

The smoothing (adaptive , learning) parameter is of importance in the adaptive filtering method . It determines the speed with which the weights in the forecasting equation are adapted to fit the historical data . In this paper , experiments were conducted to minimize intervals which contain adaptive parameter in several situations for autoregressive (AR) processes