Filtered gradient algorithms applied to a subband adaptive filter structure
Adaptive filtering techniques in subbands have been recently developed for a number of applications including acoustic echo cancellation and wideband active noise control. In such applications, hundreds of taps are required resulting in high computational complexity and low convergence rate when using LMS-based algorithms. For fullband systems, new algorithms which try to overcome these drawbacks have been investigated. A class of these algorithms employing variants of the filtered gradient adaptive (FGA) algorithm has been successfully developed. We apply these techniques to a recently proposed subband adaptive filter structure in order to improve the convergence rate and the computational load. Computer simulations show the benefits obtained with these proposed algorithms.