Development of the RLS algorithm based on the iterative equation solvers

In this paper we propose an approach towards developing a RLS algorithm that is based on the iterative techniques for solution of the linear system of equations. Two such fundamental methods namely the Steepest Descent and the Gauss-Seidel algorithms are used to solve the least squares normal equations. Simple optimization is presented to reduce the overall complexity of the algorithm and not compromising on the performance. Simulation results are compared with those of the classical RLS algorithm and it is shown that the proposed algorithm gives convergence results similar to those of Classical RLS with the added advantage of reduce computational complexity.