Improvement of the convergence speed and the tracking ability of the fast Newton type adaptive filtering (FNTF) algorithm

In this paper, five new versions of the fast Newton type adaptive filtering (FNTF) algorithm are presented. A brief preliminary presentation of these algorithms was given in Djendi et al. [Comparative study of new version of the Newton type adaptive filtering algorithm, in: Proceedings of the IEEE ICASSP 2004, Montreal, Canada, May 2004, pp. 677–680]. The first algorithm is based on a simple modification of the filtering part, by introducing a scalar accelerator parameter. The second algorithm is based on the use of the temporal subdivision technique to update the local filter coefficients. The third algorithm is a modification of the second one, by the use of the final filtering errors to update the filter coefficients. The fourth and the fifth algorithms are based, respectively, on the combination of features from the first algorithm with features of the second and third algorithms. These new algorithms are proposed to improve the convergence speed of the original version of the FNTF algorithm for the identification of acoustic impulse responses, and also to improve the tracking ability when the systems vary in time. A comparative study of each algorithm with the original version of the FNTF algorithm is also presented.