document: Estimation of an N-L-N Hammerstein-Wiener model Estimation of a single-input single-output block-oriented model is studied . The model consists of a linear block embedded between two static nonlinear gains . Hence , it is called an N-L-N Hammerstein-Wiener model . First , the model structure is motivated and the disturbance model is discussed . The paper then concentrates on parameter estimation . A relaxation iteration scheme is proposed by making use of a model structure in which the error is bilinear-in-parameters . This leads to a simple algorithm which minimizes the original loss function . The convergence and consistency of the algorithm are studied . In order to reduce the variance error , the obtained linear model is further reduced using frequency weighted model reduction . A simulation study is used to illustrate the method
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