An improved FTRLS filtering algorithm and its simulation analysis

Abstract

Due to the large error of LMS algorithm and the slow convergence rate, the recursive least squares (RLS) algorithm is proposed. Although the recursive estimation error is greatly reduced, the convergence rate is one order of magnitude higher than that of the general LMS filter. When the order N increases, the amount of calculation for a single iteration of the RLS algorithm is increased significantly. Aiming at these problems, this paper proposes an improved FTRLS filtering algorithm, which is to find out the amount of large error and accumulate the error, and then make the error feedback to make the algorithm more stable. The analysis of MATLAB simulation results show that the improved algorithm can improve the convergence speed and stability of the algorithm, and effectively reduce the convergence of the noise.