J. S. Bendat, Nonlinear system analysis and identification from random data, 1990.

S. Boyd and L. O. Chua, Fading memory and the problem of approximating nonlinear operators with Volterra series, IEEE Transactions on Circuits and Systems, vol.32, issue.11, pp.1150-1161, 1985.
DOI : 10.1109/TCS.1985.1085649

J. D. Caroll and J. J. Chang, Analysis of individual differences in multidimensional scaling via an n-way generalization of ???Eckart-Young??? decomposition, Psychometrika, vol.12, issue.3, pp.283-319, 1970.
DOI : 10.1007/BF02310791

H. Chen, Modeling and identification of parallel nonlinear systems: Structural classification and parameter estimation methods, Proc. of the IEEE, pp.39-66, 1995.

P. Comon, Tensor decompositions: state of the art and applications, IMA Conf. Mathematics in Signal Processing, 2000.
URL : https://hal.archives-ouvertes.fr/hal-00347139

K. Feher, Digital communications-Satellite/Earth station engineering, 1993.

G. B. Giannakis and E. Serpedin, A bibliography on nonlinear system identification, Signal Processing, vol.81, issue.3, pp.533-580, 2001.
DOI : 10.1016/S0165-1684(00)00231-0

R. Haber, Structural identification of quadratic block-oriented models based on estimated Volterra kernels, International Journal of Systems Science, vol.20, issue.8, pp.1355-1380, 1989.
DOI : 10.1016/0005-1098(69)90032-6

R. A. Harshman, Foundation of the PARAFAC procedure: models and conditions for an " explanatory " multimodal factor analysis. UCLA working papers in phonetics, pp.1-84, 1970.

H. Tan and K. Godfrey, Identification of Wiener-Hammerstein models using linear interpolation in the frequency domain (LIFRED), IEEE Transactions on Instrumentation and Measurement, vol.51, issue.3, pp.509-521, 2002.
DOI : 10.1109/TIM.2002.1017722

A. D. Kalafatis, L. Wang, and W. R. Cluett, Identification of Wiener-type nonlinear systems in a noisy environment, International Journal of Control, vol.66, issue.6, pp.923-941, 1997.
DOI : 10.1080/002071797224469

R. E. Kearney, R. B. Stein, and L. Parameswaran, Identification of intrinsic and reflex contributions to human ankle stiffness dynamics, IEEE Transactions on Biomedical Engineering, vol.44, issue.6, pp.493-504, 1997.
DOI : 10.1109/10.581944

A. Y. Kibangou and G. Favier, Wiener-Hammerstein systems modeling using diagonal Volterra kernels coefficients, IEEE Signal Proc. Letters, pp.381-384, 2006.
DOI : 10.1109/LSP.2006.871705
URL : https://hal.archives-ouvertes.fr/hal-00417644

A. Y. Kibangou and G. Favier, A non-iterative solution for PARAFAC decomposition with Toeplitz constraints, 2008.

T. G. Kolda and B. W. Bader, Tensor Decompositions and Applications, SIAM Review, vol.51, issue.3, 2009.
DOI : 10.1137/07070111X
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.130.782

M. J. Korenberg and I. W. Hunter, The identification of nonlinear biological systems: LNL cascade models, Biological Cybernetics, vol.55, pp.125-134, 1986.

P. Z. Marmarelis and K. Naka, Identification of multiinput biological systems, IEEE Trans. on Biomedical Engineering, vol.21, issue.2, pp.88-101, 1974.

N. D. Sidiropoulos, R. Bro, and G. B. Giannakis, Parallel factor analysis in sensor array processing, IEEE Transactions on Signal Processing, vol.48, issue.8, pp.2377-2388, 2000.
DOI : 10.1109/78.852018

G. Vandersteen and J. Schoukens, Measurement and identification of nonlinear systems consisting of linear dynamic blocks and one static nonlinearity, IEEE Transactions on Automatic Control, vol.44, issue.6, pp.1266-1271, 1999.
DOI : 10.1109/9.769388

M. Weiss, C. Evans, and D. Rees, Identification of nonlinear cascade systems using paired multisine signals, IEEE Transactions on Instrumentation and Measurement, vol.47, issue.1, pp.332-336, 1998.
DOI : 10.1109/19.728844