Design of hybrid nonlinear spline adaptive filters for active noise control

This paper introduces a class of hybrid nonlinear spline filters, which are designed as a cascade of an adaptive spline activation function and a single layer adaptive nonlinear network. The adaptive nonlinear networks employed in this work are the functional link network (FLN) and the even mirror Fourier nonlinear (EMFN) network. Suitable update rules, which not only update the adaptive weights of the nonlinear networks, but also introduce adaptability in the developed spline function. The proposed nonlinear filters have been successfully applied to nonlinear system identification as well as nonlinear active noise control. The new filters have been shown to outperform the other popular nonlinear filters compared in the study.