Partial update even mirror fourier non-linear filters for active noise control

A non-linear active noise control (ANC) scheme, which is based on an even mirror Fourier non-linear filter has been developed in this paper. A new weight update mechanism for the proposed scheme has been suggested and the range of the learning rate which ensures stability has been derived. The noise mitigation achieved using the new scheme has been compared with that obtained using a functional link artificial neural network (FLANN) based ANC system as well as using a generalized FLANN (GFLANN) based ANC mechanism. The computational complexity of the proposed algorithm has been further reduced by using the concept of partial update signal processing. A simulation study has been carried out to evaluate the effectiveness of the new method. Improved noise reduction at reduced computational load has been provided by the new partial update ANC scheme proposed.