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In this paper, special two-stage input signal based neuro-fuzzy model for Hammerstein-Wiener processes is presented. The input and output nonlinear static parts of the Hammerstein-Wiener process are described by two independent neuro-fuzzy models without any prior process knowledge, thus avoiding the inevitable restrictions on static nonlinear function encountered by using the polynomial approach. To construct the neuro-fuzzy based Hammerstein-Wiener model, special two-stage input signal is carried out, and an analytical solution is developed to calculate the parameters of the linear dynamic part and two static nonlinear functions. Examples are used to illustrate the applicability of the proposed method and a comparison with polynomial approach is made.