The block algorithm has illustrated significant improvement in performance over the NLMS algorithm. However, it is known that block processing algorithms have lower tracking capabilities than their sample-by-sample counterparts. The fast affine projection (FAP) algorithm also outperforms the NLMS with a slight increase in complexity, but involves the fast calculation of the inverse of a covariance matrix of the input data that could undermine the performance of the algorithm. In this paper, we present a sample-by-sample version of the block algorithm and develop a low complexity implementation of this algorithm using a similar approach to the FAP algorithm. The new fast algorithm does not require matrix inversion thus alleviating the drawbacks of the FAP algorithm. A variable step size version of the proposed algorithm is also presented.
['Khaled A. Mayyas', 'Tyseer Aboulnasr']
A fast weighted subband adaptive algorithm