A fast convergence algorithm for adaptive FIR filters with coarsely located taps

A fast convergence algorithm for adaptive FIR (finite impulse response) filters with coarsely located taps is proposed. The algorithm has two-stage adaptation and tap-position control with a constraint on the region. The two-stage adaptation includes estimation of the flat delay of the impulse response and coefficient adaptation with independent tap-position control. The constrained tap-position control is achieved by imposing a limit on new-tap-position search. Assuming an echo canceler application, performance in single-talk was evaluated by means of a white Gaussian signal. The algorithm reduces the convergence speed by up to 80% over both STWQ (scrub taps waiting in a queue) and the full-tap NLMS (normalized least mean square) and always provides faster convergence speed than the full-tap NLMS. The proposed algorithm is applicable to adaptive FIR filters to model a path with long flat delay, such as echo cancelers for satellite communications