This paper proposes a fast convergence algorithm for adaptive FIR filters with sparse taps. Coefficient values and positions are simultaneously controlled. The proposed algorithm consists of two stages： flat-delay estimation and tapposition control with a constraint. The flat-delay estimation is carried out by estimating the significant dispersive region of the impulse response. The constrained tap-position control is achieved by imposing a limit on the new-tap-position search. Simulation results show that the proposed algorithm reduces the convergence speed by up to 85% over the conventional algorithms for a white signal input. For a colored signal, it also converges in 40% of the convergence time by the conventional algorithms. The proposed algorithm is applicable to adaptive FIR filters which are to model a path with long flat delay, such as echo cancelers for satellite-link communications.

This paper proposes an adaptive noise canceller with low signal-distortion in the presence of crosstalk. The proposed noise canceller has two pairs of cross-coupled adaptive filters, each of which consists of the main filter and a sub filter. The signal-to-noise ratios (SNRs) of the primary and the reference signals are estimated by the sub filters. To reduce signal distortion at the output of the adaptive noise canceller, the step sizes for coefficient adaptation in the main filters are controlled according to the estimated SNRs. Computer simulation results show that the proposed noise canceller reduces signal distortion in the output signal by up to 15 dB compared to the conventional noise canceller.