G. Lonnbark, Characterization of track irregularities with respect to vehicle response, Royal Institute of Technology, 2012.

G. Perrin, C. Soize, D. Duhamel, and C. Funfschilling, Track irregularities stochastic modeling, Probabilistic Engineering Mechanics, vol.34, pp.123-130, 2013.
DOI : 10.1016/j.probengmech.2013.08.006

URL : https://hal.archives-ouvertes.fr/hal-00850645

N. Lestoille, C. Soize, G. Perrin, and F. Funfschilling, Long Time Evolution of Train Dynamics with Respect to Track Irregularities, Proceedings of The 2. International Congress on Railway Technology, pp.8-11, 2014.

G. Perrin, Random fields and associated statistical inverse problems for uncertainty quantifications -Applications to railway track geometries for high-speed trains dynamical responses and risk assessment, Ph. D. Diss, 2013.

G. Perrin, C. Soize, D. Duhamel, and C. Funfschilling, Quantification of the influence of the track geometry variability on the train dynamics, Mechanical System and Signal processing, 2015.

G. Foeillet, F. Coudert, and V. Delcourt, IRIS 320 is a global concept inspection vehicle merging engineering and R&D tools for infrastructure maintenance, Proceedings of the Eight World Congress on Railway Research, 2008.

F. Coudert and B. Richard, IRIS 320 GEOV: a new track geometry recoding system designed continuing on from the Mauzin track recording coaches, Revue Générale des Chemins de Fer, pp.7-22, 2009.

H. B. Zheng, Q. S. Yan, J. L. Hu, and Z. Chen, Numerical simulation of railway track irregularities based on stochastic expansion method of standard orthogonal basis, Applied Mechanics and Materials, vol.178, pp.1373-1378, 2012.

R. N. Iyengar and O. R. , A new model for non-Gaussian random excitations, Probabilistic Engineering Mechanics, vol.8, issue.3-4, pp.281-287, 1993.
DOI : 10.1016/0266-8920(93)90022-N

X. Lei and N. A. Noda, ANALYSES OF DYNAMIC RESPONSE OF VEHICLE AND TRACK COUPLING SYSTEM WITH RANDOM IRREGULARITY OF TRACK VERTICAL PROFILE, Journal of Sound and Vibration, vol.258, issue.1, pp.147-165, 2002.
DOI : 10.1006/jsvi.2002.5107

A. Hamid and A. Gross, Track-quality indices and track-degradation models for maintenance-of-way planning, Transportation Research Record, Journal of the Transport Research Board, vol.802, pp.2-8, 1981.

G. Perrin, C. Soize, D. Duhamel, and C. Funfschilling, MODELING THE TRACK GEOMETRY VARIABILITY, Proceedings of 10th World Congress on Computational Mechanics, 2012.
DOI : 10.5151/meceng-wccm2012-16655

URL : https://hal.archives-ouvertes.fr/hal-00734159

G. Perrin, C. Soize, D. Duhamel, and C. Funfschilling, Identification of Polynomial Chaos Representations in High Dimension from a Set of Realizations, SIAM Journal on Scientific Computing, vol.34, issue.6, pp.2917-2945, 2012.
DOI : 10.1137/11084950X

URL : https://hal.archives-ouvertes.fr/hal-00770006

C. Soize, Identification of high-dimension polynomial chaos expansions with random coefficients for non-Gaussian tensor-valued random fields using partial and limited experimental data, Computer Methods in Applied Mechanics and Engineering, vol.199, issue.33-36, pp.2150-2164, 2010.
DOI : 10.1016/j.cma.2010.03.013

URL : https://hal.archives-ouvertes.fr/hal-00684324

G. Perrin, C. Soize, D. Duhamel, and C. Funfschilling, Karhunen???Lo??ve expansion revisited for vector-valued random fields: Scaling, errors and optimal basis., Journal of Computational Physics, vol.242, issue.1, pp.607-622, 2013.
DOI : 10.1016/j.jcp.2013.02.036

URL : https://hal-upec-upem.archives-ouvertes.fr/hal-00805616/file/publi-2013-JCP-242_1_607-622-perrin-soize-duhamel-funfschilling-preprint.pdf

G. Perrin, C. Soize, D. Duhamel, and C. Funfschilling, A Posteriori Error and Optimal Reduced Basis for Stochastic Processes Defined by a Finite Set of Realizations, SIAM/ASA Journal on Uncertainty Quantification, vol.2, issue.1, pp.745-762, 2014.
DOI : 10.1137/130905095

URL : https://hal.archives-ouvertes.fr/hal-01097139

G. R. Terrell and D. W. Scott, Variable Kernel Density Estimation, The Annnals of Statistics, pp.1236-1265, 1992.

A. W. Bowman and W. Azzalini, Applied Smoothing Techniques for Data Analysis, 1997.

S. Kraft, Parameter identification for a TGV model, 2012.
URL : https://hal.archives-ouvertes.fr/tel-00731143

C. Soize, Stochastic Models of Uncertainties in Computational Mechanics, ASCE
DOI : 10.1061/9780784412237

URL : https://hal.archives-ouvertes.fr/hal-00749201

R. Ghanem and P. Spanos, Stochastic finite elements: a spectral approach, 1991.
DOI : 10.1007/978-1-4612-3094-6

O. Le-maitre and O. Knio, Spectral Methods for Uncertainty Quantification, 2010.
DOI : 10.1007/978-90-481-3520-2