Adaptive volterra fillers for active control of nonlinear noise processes

This paper presents a Volterra filtered-X least mean square (LMS) algorithm for feedforward active noise control, The recent research has demonstrated that linear active noise control (ANC) systems can be successfully applied to reduce the broadband noise and narrowband noise. Specifically, such lin ear ANC systems are very efficient in reduction of low-frequency noise. How ever, in some situations, the noise that comes from a dynamic system may be a nonlinear and deterministic noise process rather than a stochastic, whit e, or tonal noise process, and the primary noise at the canceling point may exhibit the nonlinear distortion, Furthermore, the secondary path estimate in the ANC system, which denotes the transfer function between the seconda ry source (secondary speaker) and the error microphone, may have nonminimum phase, and hence, the causality constraint is violated. If such situations exist, the linear ANC system will suffer performance degradation. In this paper, an implementation of a Volterra filtered-X LMS (VFXLMS) algorithm ba sed on a multichannel structure is described for feedforward active noise c ontrol. Numerical simulation results show that the developed algorithm achi eves performance improvement over the standard filtered-X LMS algorithm for the following two situations: I) The reference noise is a nonlinear noise process, and at the same time, the secondary path estimate is of nonminimum phase; 2) the primary path exhibits the nonlinear behavior. In addition, t he developed VFXLMS algorithm can also be employed as an alternative in the case where the standard filtered-X LMS algorithm does not perform well.