Identification of Hammerstein model using functional link artificial neural network
A novel FLANN based method for identifying Hammerstein model is proposed. FLANN is used to represent the static nonlinear part of Hammerstein model. LM algorithm is derived to learn the weights of FLANN. Linear and nonlinear parts are identified separately using specified input signal. Numerical results verify the effectiveness of the proposed method.
identification hammerstein model functional link artificial neural network