A Fast SSCF Adaptive Algorithm and Its Application to Adaptive Equalizer

Abstract

The problem of the series type adaptive filter using LMS algorithm is the bias error of the tap gain caused by the noise. In this paper we consider a noise free fast SSCF (Square Sum of Correlation Function) adaptive algorithm with white input signal and its application to the adaptive equalizer. The comparison of the convergence speed to LMS and SSCF adaptive algorithm is presented. The convergence of the adaptive algorithm is guaranteed under the assumption of the uncorrelated property of the noise and the white input signal. Finally, these results of the theoretical consideration are verified by computer simulation.