Implementation of RLS Algorithm |
An algorithm for recursively calculating the least square solution to adaptive filter, for its
Ajmera HV, Ahmed MZ
implementation on a dsPIC is described in this paper. It shows an unified approach for
deriving the fixed-point Recursive Least Square (RLS) algorithm to estimate the optimal set of
filter coefficients. The objective is to study implementation effects on the Recursive Least
Square algorithm used in the mean-square manner for adaptive filter for a dsPIC. Using the
matrix operation as well as the round-off error model, the effects of machine implementation
on RLS algorithm has being found out theoretically confirmed by simulation results. The main
sources of errors can be thought of: division operation involved in updating filter variables.
Due to such errors, the digitally implemented algorithm shows a divergence rather than
convergence. A couple of solutions are provided to give better performance, so that the
simulated results for filter coefficients for fixed and floating point are found to be similar.