Equivalency of SSCF Adaptive Algorithm to Noise Free LMS Adaptive Algorithm

Abstract

In this paper, an equivalency of the SSCF (Square Sum of Correlation Function) adaptive algorithm to the noise free LMS (Least Mean Square) adaptive algorithm is considered. It is known that the SSCF adaptive algorithm estimating the inverse transfer function of the unknown system is robust for the sound noise added at the input. It is shown that the SSCF adaptive algorithm is equivalent to the noise free LMS adaptive algorithm if the input signal is white and the number of the square sum of correlation function satisfies the certain condition. The numerical verifications of the theoretical consideration are also presented.