Hammerstein Spline Adaptive Filtering based on Normalised Least Mean Square Algorithm

This paper proposes a normalised least mean square algorithm based on Hammerstein spline adaptive filtering. A nonlinear Hammerstein adaptive filters consists of memory-less function modified during learning and the spline control point is automatically controlled by gradient-based method. Simulation results demonstrate that the proposed algorithm exhibits more robust performance compared with the conventional spline adaptive filtering algorithms.