J. Hérault and C. Jutten, Space or time adaptive signal processing by neural network models, AIP Conference Proceedings, pp.206-211, 1987.
DOI : 10.1063/1.36258

P. Comon and C. Jutten, Handbook of Blind Source Separation: Independent component analysis and applications. Academic press, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00460653

T. Mei, F. Yin, and J. Wang, Blind Source Separation Based on Cumulants With Time and Frequency Non-Properties, IEEE Transactions on Audio, Speech, and Language Processing, vol.17, issue.6, pp.1099-1108, 2009.
DOI : 10.1109/TASL.2009.2019924

P. Comon, Independent component analysis, A new concept?, Signal Processing, vol.36, issue.3, pp.287-314, 1994.
DOI : 10.1016/0165-1684(94)90029-9
URL : https://hal.archives-ouvertes.fr/hal-00417283

A. J. Bell and T. J. Sejnowski, An Information-Maximization Approach to Blind Separation and Blind Deconvolution, Neural Computation, vol.20, issue.1, pp.1129-1159, 1995.
DOI : 10.1109/78.301850

J. F. Cardoso and A. Souloumiac, An efficient technique for the blind separation of complex sources, [1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics, pp.275-279, 1993.
DOI : 10.1109/HOST.1993.264552

J. F. Cardoso and B. H. Laheld, Equivariant adaptive source separation, IEEE Transactions on Signal Processing, vol.44, issue.12, pp.3017-3030, 1996.
DOI : 10.1109/78.553476
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.49.7924

L. De-lathauwer, B. De, J. Moor, and . Vandewalle, ) Approximation of Higher-Order Tensors, SIAM Journal on Matrix Analysis and Applications, vol.21, issue.4, pp.1324-1342, 2000.
DOI : 10.1137/S0895479898346995

A. Hyvärinen, Fast and robust fixed-point algorithms for independent component analysis, IEEE Transactions on Neural Networks, vol.10, issue.3, pp.626-634, 1999.
DOI : 10.1109/72.761722

L. Tong, V. C. Soon, Y. F. Huang, and R. Liu, AMUSE: a new blind identification algorithm, IEEE International Symposium on Circuits and Systems, pp.1784-1787, 1990.
DOI : 10.1109/ISCAS.1990.111981

L. Tong, R. W. Liu, V. C. Soon, and Y. F. Huang, Indeterminacy and identifiability of blind identification, IEEE Transactions on Circuits and Systems, vol.38, issue.5, pp.499-509, 1991.
DOI : 10.1109/31.76486

A. Belouchrani, K. Abed-meraim, J. Cardoso, and E. Moulines, A blind source separation technique using second-order statistics, IEEE Transactions on Signal Processing, vol.45, issue.2, pp.434-444, 1997.
DOI : 10.1109/78.554307

M. Golbabaee, S. Arberet, and P. Vandergheynst, Compressive Source Separation: Theory and Methods for Hyperspectral Imaging, IEEE Transactions on Image Processing, vol.22, issue.12, pp.5096-5110, 2013.
DOI : 10.1109/TIP.2013.2281405

I. Meganem, P. Deliot, X. Briottet, Y. Deville, and S. Hosseini, Physical modelling and non-linear unmixing method for urban hyperspectral images, 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), pp.1-4, 2011.
DOI : 10.1109/WHISPERS.2011.6080863

L. T. Duarte and C. Jutten, Design of Smart Ion-Selective Electrode Arrays Based on Source Separation through Nonlinear Independent Component Analysis, Oil & Gas Science and Technology ??? Revue d???IFP Energies nouvelles, vol.69, issue.2, pp.293-306, 2014.
DOI : 10.2516/ogst/2013194
URL : https://hal.archives-ouvertes.fr/hal-00962227

F. Merrikh-bayat, M. Babaie-zadeh, and C. Jutten, Linear-quadratic blind source separating structure for removing show-through in scanned documents, International Journal on Document Analysis and Recognition (IJDAR), vol.85, issue.5, pp.319-333, 2011.
DOI : 10.1016/j.sigpro.2004.11.021
URL : https://hal.archives-ouvertes.fr/hal-00643471

M. Babaie-zadeh, On blind source separation in convolutive and nonlinear mixtures, 2002.

T. Blaschke, T. Zito, and L. Wiskott, Independent Slow Feature Analysis and Nonlinear Blind Source Separation, Neural Computation, vol.19, issue.4, pp.994-1021, 2007.
DOI : 10.1162/jmlr.2003.4.7-8.1319
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.304.7283

D. N. Levin, Performing Nonlinear Blind Source Separation With Signal Invariants, IEEE Transactions on Signal Processing, vol.58, issue.4, pp.2131-2140, 2010.
DOI : 10.1109/TSP.2009.2034916

A. Taleb and C. Jutten, Source separation in post-nonlinear mixtures, IEEE Transactions on Signal Processing, vol.47, issue.10, pp.2807-2820, 1999.
DOI : 10.1109/78.790661

Y. Altmann, A. Halimi, N. Dobigeon, and J. Y. Tourneret, Supervised Nonlinear Spectral Unmixing Using a Postnonlinear Mixing Model for Hyperspectral Imagery, IEEE Transactions on Image Processing, vol.21, issue.6, pp.3017-3025, 2012.
DOI : 10.1109/TIP.2012.2187668

A. Halimi, Y. Altmann, N. Dobigeon, and J. Y. Tourneret, Nonlinear Unmixing of Hyperspectral Images Using a Generalized Bilinear Model, IEEE Transactions on Geoscience and Remote Sensing, vol.49, issue.11, pp.4153-4162, 2011.
DOI : 10.1109/TGRS.2010.2098414

Y. Deville and L. T. Duarte, An Overview of Blind Source Separation Methods for Linear-Quadratic and Post-nonlinear Mixtures, International Conference on Latent Variable Analysis and Signal Separation, pp.155-167, 2015.
DOI : 10.1007/978-3-319-22482-4_18

A. Hyvärinen and P. Pajunen, Nonlinear independent component analysis: Existence and uniqueness results, Neural Networks, vol.12, issue.3, pp.429-439, 1999.
DOI : 10.1016/S0893-6080(98)00140-3

A. M. Kagan, Y. V. Linnik, and C. R. Rao, Extension of darmoisskitcvic theorem to functions of random variables satisfying an addition theorem, Communications in Statistics-Theory and Methods, vol.1, issue.5, pp.471-474, 1973.

S. Hosseini and C. Jutten, On the separability of nonlinear mixtures of temporally correlated sources, IEEE Signal Processing Letters, vol.10, issue.2, pp.43-46, 2003.
DOI : 10.1109/LSP.2002.807871

C. Jutten and J. Karhunen, Advances in nonlinear blind source separation, Proceeding of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA2003), pp.245-256, 2003.

B. Ehsandoust, B. Rivet, C. Jutten, and M. Babaie-zadeh, Nonlinear blind source separation for sparse sources, 2016 24th European Signal Processing Conference (EUSIPCO), pp.1583-1587, 2016.
DOI : 10.1109/EUSIPCO.2016.7760515
URL : https://hal.archives-ouvertes.fr/hal-01400546

L. T. Duarte, R. Suyama, R. Attux, J. M. Romano, and C. Jutten, A Sparsity-Based Method for Blind Compensation of a Memoryless Nonlinear Distortion: Application to Ion-Selective Electrodes, IEEE Sensors Journal, vol.15, issue.4, pp.2054-2061, 2015.
DOI : 10.1109/JSEN.2014.2371013
URL : https://hal.archives-ouvertes.fr/hal-01164752

K. Dogancay, Blind compensation of nonlinear distortion for bandlimited signals, IEEE Transactions on Circuits and Systems I: Regular Papers, vol.52, issue.9, pp.1872-1882, 2005.
DOI : 10.1109/TCSI.2005.852936

F. Arvasti and A. K. Jain, Zero crossings, bandwidth compression, and restoration of nonlinearly distorted band-limited signals, Journal of the Optical Society of America A, vol.3, issue.5, pp.651-654, 1986.
DOI : 10.1364/JOSAA.3.000651

B. Ehsandoust, M. Babaie-zadeh, and C. Jutten, Blind Source Separation in Nonlinear Mixture for Colored Sources Using Signal Derivatives, pp.193-200, 2015.
DOI : 10.1007/978-3-319-22482-4_22
URL : https://hal.archives-ouvertes.fr/hal-01226466

M. Spivak, Calculus on Manifolds: A Modern Approach to Classical Theorems of Advanced Calculus, ser. Advanced book program, 1965.

J. B. Tenenbaum, V. D. Silva, and J. C. Langford, A Global Geometric Framework for Nonlinear Dimensionality Reduction, Science, vol.290, issue.5500, pp.2319-2323, 2000.
DOI : 10.1126/science.290.5500.2319

C. H. Reinsch, Smoothing by spline functions Numerische mathematik, pp.177-183, 1967.
DOI : 10.1007/bf02169154

C. and D. Boor, A practical guide to splines, 1978.

J. Malek, Blind compensation of memoryless nonlinear distortions in sparse signals, 21st European Signal Processing Conference, pp.1-5, 2013.