E. W. Bai, R. Jr, and J. , Towards identification of Wiener systems with the least amount of a priori information on the nonlinearity, Automatica, vol.44, issue.4, pp.910-919, 2008.
DOI : 10.1016/j.automatica.2007.08.001

S. A. Billings and S. Y. Fakhouri, Identification of systems containing linear dynamic and static nonlinear elements, Automatica, vol.18, issue.1, pp.15-26, 1982.
DOI : 10.1016/0005-1098(82)90022-X

T. Chen, H. Ohlsson, and L. Ljung, On the estimation of transfer functions, regularizations and Gaussian processes???Revisited, Automatica, vol.48, issue.8, pp.1525-1535, 2012.
DOI : 10.1016/j.automatica.2012.05.026

A. Chiuso, System identification techniques: Convexification , regularization, relaxation, Encyclopedia of Systems and Control, 2014.

T. Doan, R. Litterman, and C. Sims, Forecasting and conditional projection using realistic prior distributions, Econometric Reviews, vol.73, issue.1, pp.1-100, 1984.
DOI : 10.2307/2534318

M. Enqvist and L. Ljung, Linear approximations of nonlinear FIR systems for separable input processes, Automatica, vol.41, issue.3, pp.459-473, 2005.
DOI : 10.1016/j.automatica.2004.11.016

M. Enqvist, A weighting method for approximate nonlinear system identification, 2007 46th IEEE Conference on Decision and Control, 2007.
DOI : 10.1109/CDC.2007.4434685

W. Greblicki, Nonparametric identification of Wiener systems, IEEE Transactions on Information Theory, vol.38, issue.5, p.14871493, 1992.
DOI : 10.1109/18.149500

X. L. Hu and H. F. Chen, Strong consistence of recursive identification for Wiener systems, Automatica, vol.41, issue.11, pp.41-1905, 2005.
DOI : 10.1016/j.automatica.2005.06.006

G. Kitagawa and H. Gersh, A smothness priorsstate space modeling of time series with trends and seasonalities, Journal of the American Statistical Association, vol.79, pp.378-389, 1984.

B. Ni, M. Gilson, Q. Zhang, and H. Garnier, A Kalman pre-filtered IV-based approach to continuoustime Hammerstein-Wiener system identification, 16th IFAC Symposium on System Identification, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00751739

M. Pawlak, Z. Hasiewicz, and P. Wachel, On Nonparametric Identification of Wiener Systems, IEEE Transactions on Signal Processing, vol.55, issue.2, pp.482-492, 2007.
DOI : 10.1109/TSP.2006.885684

G. Pillonetto, D. Nicolao, and G. , A new kernel-based approach for linear system identification, Automatica, vol.46, issue.1, pp.81-93, 2010.
DOI : 10.1016/j.automatica.2009.10.031

C. P. Robert and G. Casella, Monte Carlo Statistical Methods, 2004.

J. Voros, Parameter identification of Wiener systems with discontinuous nonlinearities, Systems & Control Letters, vol.44, issue.5, pp.363-372, 2001.
DOI : 10.1016/S0167-6911(01)00155-4

A. Wills, T. Schön, L. Ljung, and B. Ninness, Identification of Hammerstein???Wiener models, Automatica, vol.49, issue.1, pp.70-81, 2013.
DOI : 10.1016/j.automatica.2012.09.018

H. K. Wong, J. Schoukens, G. , and K. R. , Analysis of Best Linear Approximation of a Wiener–Hammerstein System for Arbitrary Amplitude Distributions, IEEE Transactions on Instrumentation and Measurement, vol.61, issue.3, pp.61-645, 2012.
DOI : 10.1109/TIM.2011.2169615

Q. Zhang, A. Iouditski, and L. Ljung, IDENTIFICATION OF WIENER SYSTEM WITH MONOTONOUS NONLINEARITY, 14th IFAC Symposium on System Identification (SYSID), 2006.
DOI : 10.3182/20060329-3-AU-2901.00020
URL : https://hal.archives-ouvertes.fr/hal-00854858

Q. Zhang and V. Laurain, Wiener system identification by weighted principal component analysis, 2014 European Control Conference (ECC), 2014.
DOI : 10.1109/ECC.2014.6862373
URL : https://hal.archives-ouvertes.fr/hal-01059203

Y. Zhu, Distillation column identification for control using Wiener model, American Control Conference, pp.3462-3466, 1999.