Normalized least mean squared adaptive algorithm with fractional tap (FT) length [articol]

Abstract

This paper illustrates a new fractional tap length (FT) algorithm that improves the performance of the normalized least mean squared (NLMS) algorithms. The proposed algorithm, named NLMS-FT, is compared with an adaptive fractional tap length algorithm named NLMS-FT (adaptive length). The computational effort is similar for the proposed and adaptive tap length algorithms but the proposed algorithm has better performance in terms of tracking capabilities, speed of convergence and miss-adjustment. The proposed algorithm has the advantage that it is a less sensitive to its parameters (that is, it has fewer control variables to set). Therefore, the proposed algorithm is more robust than the adaptive tap length algorithm.