A fast weighted subband adaptive algorithm

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