Adaptive combination of FLANN filters and its application to nonlinear ANC systems

To alleviate the tradeoff between the convergence rate and steady state error, an adaptive convex combination scheme-based adaptive FLANN filter is proposed for nonlinear ANC systems in this paper. The mixing parameter that controls the combination strategy is adapted to minimize the error of the overall filter by the gradient descent approach. Simulation results demonstrate that the proposed CFSLMS algorithm can achieve both fast convergence rate and low steady state error in comparison with the conventional FSLMS algorithm for nonlinear ANC systems.

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