A Delayless Adaptive IFIR Filterbank Structure for Active Noise Control

Active noise control (ANC) applications involve adaptive filters with hundreds of taps. These filters are associated with high computational burden depending on the number of taps in the filter and may suffer from slow convergence if the reference signal spectrum has a large dynamic range. Subband and filterbank techniques have been proposed to address these problems. Filter bank adaptive filter (FBAF) is one of the models, which can model a linear system exactly. The FBAF model is a parallel bank of filters with each bank (channel) comprising of cascade of a set of short length filter called interpolator followed by a sparse model filter. Each channel consisting of the interpolator filter and sparse model filter is identical to a classical IFIR filter, hence the structure is called adaptive IFIR filterbank structure. The filterbank basis functions are orthonormal, which introduce delay in the signal path degrading the performance of the adaptive filter. In this paper, we propose a delayless adaptive filterbank structure based on IFIR filterbank structure for active noise control. The proposed delayless adaptive filter has improved convergence rate and shows better noise cancellation in the wideband and narrowband ANC domain when compared with the conventional fullband adaptive structure. The computational complexity of the proposed structure is compared with the fullband structure.