A novel 2-D adaptive filter based on the 1-D RLS algorithm

This paper proposes a novel two-dimensional (2-D) adaptive filter by applying a 1-D recursive least-squares (RLS) algorithm along both horizontal and vertical directions. The relation of the proposed algorithm to a usual 2-D RLS algorithm are investigated. A method that employs a priori estimation error is also considered to accelerate the convergent rate of the algorithm. The proposed filter has a good performance in nonstationary case, and the accuracy of convergence is better than in the existing 2-D least mean square (LMS) adaptive filters. The amount of computations required for the proposed algorithm are relatively small. Finally, an example is given to illustrate the utility of the proposed filter.