New combinatorial methods for the improvement of the convergence speed and the tracking ability of the fast stable RLS adaptive algorithm

Abstract

In this paper, we present new versions of the fast RLS adaptive algorithm. These versions are based on a combination of the block filtering technique and a use of a scalar accelerator parameter in each block. These mixing techniques lead a faster convergence of the fast RLS algorithm and behave better with time-varying acoustic systems. The proposed versions have approximately the same complexity of calculation than the original version of the fast RLS algorithm. The difference between this work and the previous ones (Benallal A. et al., Jan 1989) is the use of a new combination techniques which provide new forms of the fast RLS prediction part. All the proposed versions and their simulations results are presented.