Fast surface-search algorithm for adaptive FIR filtering

This paper proposes a fast surface search (FSS) algorithm for adaptive FIR filtering. The proposed algorithm depends on the efficient calculation of the fast gain vector (FGA) defined in C. E. Davila (July 1993) and the rank-one updating formula of the correlation matrix of the input vector sequence. This algorithm is of computational complexity O(M), which is comparable with the fast recursive least squares transversal filters for adaptive FIR filtering. The global convergence of the proposed algorithm is studied by the Lyapunov indirect method. The performances of the relative algorithms are shown via computer simulations.