Adaptive Nonlinear FIR Active Noise Control

A nonlinear FIR active noise controller based on functional mapping is proposed for nonlinear active noise control (ANC) systems, which simplifies the Volterra filter inspiring from Hammerstein/Wiener model. The generalized filtered-X gradient descent algorithm is applied to the proposed controller for the nonlinear, non-Gaussian noises attenuation, which is based on the weighted sum of Renyis quadratic error entropy and mean square error. In addition, the convergence of the proposed approach is analyzed. The overall scheme integrates the advantages of information entropy and mean square error criterion, and it also has the advantages of relative simple structure and less learning parameters. The simulation results demonstrate the validity of the proposed approach.