Design and implementation of a nonlinear Acoustic Echo Canceller

In this paper, an Acoustic Echo Canceller based on Neural Networks and a Fast Affine Projection (FAP) algorithm has been introduced. This structure allows a large set of trade-offs between convergence rate, residual error, tracking capacity, and arithmetic complexity. Hence, the proposed structure has the potential for solving another difficult nonlinear adaptive signal processing tasks; such as system identification where nonlinearity and nonstationarity are both important factors. To investigate the feasibility of practical implementation of the proposed structure, a Hardware/Software implementation is discussed. The specific objective is to find an implementation that satisfies all the system design constraints at least cost.