P. Comon and C. Jutten, Handbook of Blind Source Separation: Independent Component Analysis and Applications, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00460653

A. Cichocki and S. Amari, Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications, 2002.
DOI : 10.1002/0470845899

S. Choi, A. Cichocki, H. Park, and S. Lee, Blind source separation and independent component analysis: A review, Neural Information Processing - Letters and Reviews, vol.6, issue.1, pp.1-57, 2005.

S. L. Robinette, R. Bruschweiler, F. C. Schroeder, and A. S. Edison, NMR in Metabolomics and Natural Products Research: Two Sides of the Same Coin, Accounts of Chemical Research, vol.45, issue.2, pp.288-297, 2012.
DOI : 10.1021/ar2001606

A. E. Taggi, J. Meinwald, and F. C. Schroeder, A New Approach to Natural Products Discovery Exemplified by the Identification of Sulfated Nucleosides in Spider Venom, Journal of the American Chemical Society, vol.126, issue.33, pp.10364-10369, 2004.
DOI : 10.1021/ja047416n

S. B. Wursthorn, J. Krasnoff, and . Clardy, Differential analysis of 2d nmr spectra: New natural products from a pilot-scale fungal extract library, Angewandte Chemie International Edition, vol.46, issue.6, pp.901-904, 2007.

D. V. Rubtsov and J. L. Griffin, Time-domain Bayesian detection and estimation of noisy damped sinusoidal signals applied to NMR spectroscopy, Journal of Magnetic Resonance, vol.188, issue.2, pp.367-379, 2007.
DOI : 10.1016/j.jmr.2007.08.008

D. V. Rubtsov, C. Waterman, R. A. Currie, C. Waterfield, J. D. Salazar et al., H NMR Spectra to Assessing the Metabolic Effects of Acute Phenobarbital Exposure in Liver Tissue, Analytical Chemistry, vol.82, issue.11, pp.4479-4485, 2010.
DOI : 10.1021/ac100344m

T. Ye, C. Zheng, S. Zhang, G. A. Gowda, O. Vitek et al., H Nuclear Magnetic Resonance Spectra of Mixtures, Analytical Chemistry, vol.84, issue.2, pp.994-1002, 2012.
DOI : 10.1021/ac202548n

O. Beckonert, H. C. Keun, T. M. Ebbels, J. Bundy, E. Holmes et al., Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts, Nature Protocols, vol.6, issue.11, pp.2692-2703, 2007.
DOI : 10.1038/nprot.2007.376

M. Reddy, G. N. , R. Ballesteros, G. , J. Lacour et al., Determination of Labile Chiral Supramolecular Ion Pairs by Chromatographic NMR Spectroscopy, Angewandte Chemie International Edition, vol.48, issue.11, pp.3255-3258, 2013.
DOI : 10.1002/anie.201209616

URL : https://hal.archives-ouvertes.fr/hal-00816608

M. R. and S. Caldarelli, Demixing of severely overlapping nmr spectra through multiple-quantum nmr, Analytical Chemistry, vol.82, issue.8, pp.3266-3269, 2010.

G. N. Manjunatha-reddy and S. Caldarelli, Improved excitation uniformity in multiple-quantum NMR experiments of mixtures, Magnetic Resonance in Chemistry, vol.50, issue.4, pp.240-244, 2013.
DOI : 10.1002/mrc.3938

URL : https://hal.archives-ouvertes.fr/hal-00967154

G. N. Reddy and S. Caldarelli, Identification and quantification of EPA 16 priority polycyclic aromatic hydrocarbon pollutants by Maximum-Quantum NMR, The Analyst, vol.47, issue.3, pp.741-746, 2012.
DOI : 10.1039/C1AN16047H

G. N. Reddy and S. Caldarelli, Maximum-quantum (MaxQ) NMR for the speciation of mixtures of phenolic molecules, Chemical Communications, vol.173, issue.10, pp.47-4297, 2011.
DOI : 10.1039/c1cc10226e

M. Piotto, G. N. Manjunatha-reddy, and S. Caldarelli, Non-uniformly sampled Maximum Quantum spectroscopy, Journal of Magnetic Resonance, vol.213, issue.1, pp.107-111, 2011.
DOI : 10.1016/j.jmr.2011.09.016

K. Bingol and R. Bruschweiler, Multidimensional Approaches to NMR-Based Metabolomics, Analytical Chemistry, vol.86, issue.1, pp.47-57, 2014.
DOI : 10.1021/ac403520j

R. Bruschweiler, Theory of covariance nuclear magnetic resonance spectroscopy, The Journal of Chemical Physics, vol.121, issue.1, pp.409-414, 2004.
DOI : 10.1063/1.1755652

R. Bruschweiler and F. L. Zhang, Covariance nuclear magnetic resonance spectroscopy, The Journal of Chemical Physics, vol.120, issue.11, pp.5253-5260, 2004.
DOI : 10.1063/1.1647054

N. Trbovic, S. Smirnov, F. L. Zhang, and R. Bruschweiler, Covariance NMR spectroscopy by singular value decomposition, Journal of Magnetic Resonance, vol.171, issue.2, pp.277-283, 2004.
DOI : 10.1016/j.jmr.2004.08.007

F. L. Zhang and R. Bruschweiler, Spectral Deconvolution of Chemical Mixtures by Covariance NMR, ChemPhysChem, vol.5, issue.6, pp.794-796, 2004.
DOI : 10.1002/cphc.200301073

K. Bingol and R. Brueschweiler, Deconvolution of Chemical Mixtures with High Complexity by NMR Consensus Trace Clustering, Analytical Chemistry, vol.83, issue.19, pp.7412-7417, 2011.
DOI : 10.1021/ac201464y

S. L. Robinette, F. Zhang, L. Bruschweiler-li, and R. Bruschweiler, Web Server Based Complex Mixture Analysis by NMR, Analytical Chemistry, vol.80, issue.10, pp.3606-3611, 2008.
DOI : 10.1021/ac702530t

D. A. Snyder and R. Brueschweiler, Generalized Indirect Covariance NMR Formalism for Establishment of Multidimensional Spin Correlations, The Journal of Physical Chemistry A, vol.113, issue.46, pp.12898-12903, 2009.
DOI : 10.1021/jp9070168

F. Zhang, S. L. Robinette, L. Bruschweiler-li, and R. Brueschweiler, Web server suite for complex mixture analysis by covariance NMR, Magnetic Resonance in Chemistry, vol.1, issue.S1, pp.118-122, 2009.
DOI : 10.1002/mrc.2486

F. Zhang, L. Bruschweiler-li, and R. Brueschweiler, Simultaneous de Novo Identification of Molecules in Chemical Mixtures by Doubly Indirect Covariance NMR Spectroscopy, Journal of the American Chemical Society, vol.132, issue.47, pp.16922-16927, 2010.
DOI : 10.1021/ja106781r

F. Zhang and R. Brueschweiler, Robust Deconvolution of Complex Mixtures by Covariance TOCSY Spectroscopy, Angewandte Chemie International Edition, vol.77, issue.15, pp.2639-2642, 2007.
DOI : 10.1002/anie.200604599

K. Zangger and H. Sterk, Homonuclear Broadband-Decoupled NMR Spectra, Journal of Magnetic Resonance, vol.124, issue.2, pp.486-489, 1997.
DOI : 10.1006/jmre.1996.1063

M. Nilsson and G. A. Morris, Pure shift proton DOSY: diffusion-ordered 1H spectra without multiplet structure, Chemical Communications, vol.42, issue.9, pp.933-935, 2007.
DOI : 10.1039/b617761a

J. Aguilar, S. Faulkner, M. Nilsson, and G. Morris, Pure Shift 1H NMR: A Resolution of the Resolution Problem?, Angewandte Chemie International Edition, vol.106, issue.23, pp.3901-3903, 2010.
DOI : 10.1002/anie.201001107

G. A. Morris, J. A. Aguilar, R. Evans, S. Haiber, and M. Nilsson, True Chemical Shift Correlation Maps: A TOCSY Experiment with Pure Shifts in Both Dimensions, Journal of the American Chemical Society, vol.132, issue.37, pp.12770-12772, 2010.
DOI : 10.1021/ja1039715

J. A. Aguilar, M. Nilsson, and G. A. Morris, Simple Proton Spectra from Complex Spin Systems: Pure Shift NMR Spectroscopy Using BIRD, Angewandte Chemie International Edition, vol.151, issue.41, pp.9716-9717, 2011.
DOI : 10.1002/anie.201103789

J. A. Aguilar, A. A. Colbourne, J. Cassani, M. Nilsson, and G. A. Morris, Decoupling Two-Dimensional NMR Spectroscopy in Both Dimensions: Pure Shift NOESY and COSY, Angewandte Chemie International Edition, vol.49, issue.26, pp.6460-6463, 2012.
DOI : 10.1002/anie.201108888

L. Paudel, R. W. Adams, P. Kirly, J. A. Aguilar, M. Foroozandeh et al., Simultaneously Enhancing Spectral Resolution and Sensitivity in Heteronuclear Correlation NMR Spectroscopy, Angewandte Chemie International Edition, vol.151, issue.44, pp.11616-11619, 2013.
DOI : 10.1002/anie.201305709

O. Cloarec, M. Dumas, A. Craig, R. H. Barton, J. Trygg et al., H NMR Data Sets, Analytical Chemistry, vol.77, issue.5, pp.1282-1289, 2005.
DOI : 10.1021/ac048630x

S. L. Robinette, J. C. Lindon, and J. K. Nicholson, Statistical Spectroscopic Tools for Biomarker Discovery and Systems Medicine, Analytical Chemistry, vol.85, issue.11, pp.5297-5303, 2013.
DOI : 10.1021/ac4007254

L. M. Smith, A. D. Maher, O. Cloarec, M. Rantalainen, H. Tang et al., Statistical correlation and projection methods for improved information recovery from diffusionedited nmr spectra of biological samples, Analytical Chemistry, issue.15, pp.79-5682, 2007.

C. J. Jr, Diffusion ordered nuclear magnetic resonance spectroscopy: principles and applications, Progress in Nuclear Magnetic Resonance Spectroscopy, vol.34, pp.3-4, 1999.

K. F. Morris and C. S. Johnson, Diffusion-ordered two-dimensional nuclear magnetic resonance spectroscopy, Journal of the American Chemical Society, vol.114, issue.8, pp.3139-3141, 1992.
DOI : 10.1021/ja00034a071

B. R. Martini, V. A. Mandelshtam, G. A. Morris, A. A. Colbourne, and M. Nilsson, Filter diagonalization method for processing PFG NMR data, Journal of Magnetic Resonance, vol.234, issue.0, pp.125-134, 2013.
DOI : 10.1016/j.jmr.2013.06.014

G. Pages, C. Delaurent, and S. Caldarelli, Investigation of the Chromatographic Process via Pulsed-Gradient Spin???Echo Nuclear Magnetic Resonance. Role of the Solvent Composition in Partitioning Chromatography, Analytical Chemistry, vol.78, issue.2, pp.561-566, 2006.
DOI : 10.1021/ac051454n

S. Viel, F. Ziarelli, and S. Caldarelli, Enhanced diffusion-edited NMR spectroscopy of mixtures using chromatographic stationary phases, Proceedings of the National Academy of Sciences, vol.100, issue.17, pp.9696-9698, 2003.
DOI : 10.1073/pnas.1533419100

D. W. Armstrong, T. J. Ward, and A. Berthod, Micellar effects on molecular diffusion: theoretical and chromatographic considerations, Analytical Chemistry, vol.58, issue.3, pp.579-582, 1986.
DOI : 10.1021/ac00294a019

R. E. Hoffman, H. Arzuan, C. Pemberton, A. Aserin, and N. Garti, High-resolution NMR ???chromatography??? using a liquids spectrometer, Journal of Magnetic Resonance, vol.194, issue.2, pp.295-299, 2008.
DOI : 10.1016/j.jmr.2008.06.022

R. Evans, S. Haiber, M. Nilsson, and G. A. Morris, Isomer Resolution by Micelle-Assisted Diffusion-Ordered Spectroscopy, Analytical Chemistry, vol.81, issue.11, pp.4548-4550, 2009.
DOI : 10.1021/ac9005777

C. F. Tormena, R. Evans, S. Haiber, M. Nilsson, and G. A. Morris, Matrix-assisted diffusion-ordered spectroscopy: mixture resolution by NMR using SDS micelles, Magnetic Resonance in Chemistry, vol.18, issue.7, pp.550-553, 2010.
DOI : 10.1002/mrc.2621

R. W. Adams, J. A. Aguilar, J. Cassani, G. A. Morris, and M. Nilsson, Resolving natural product epimer spectra by matrix-assisted DOSY, Organic & Biomolecular Chemistry, vol.198, issue.20, pp.7062-7064, 2011.
DOI : 10.1039/c1ob06097j

F. Asaro and N. Savko, Resolution of a nonionic surfactant oligomeric mixture by means of DOSY with inverse micelle assistance, Magnetic Resonance in Chemistry, vol.133, issue.4, pp.195-198, 2011.
DOI : 10.1002/mrc.2732

A. K. Rogerson, J. A. Aguilar, M. Nilsson, and G. A. Morris, Simultaneous enhancement of chemical shift dispersion and diffusion resolution in mixture analysis by diffusion-ordered NMR spectroscopy, Chemical Communications, vol.81, issue.25, pp.7063-7064, 2011.
DOI : 10.1016/j.jmr.2011.1003.1016

C. Pemberton, R. Hoffman, A. Aserin, and N. Garti, New insights into silica-based NMR ???chromatography???, Journal of Magnetic Resonance, vol.208, issue.2, pp.262-269, 2011.
DOI : 10.1016/j.jmr.2010.11.013

C. Pemberton, R. E. Hoffman, A. Aserin, and N. Garti, NMR Chromatography Using Microemulsion Systems, Langmuir, vol.27, issue.8, pp.4497-4504, 2011.
DOI : 10.1021/la200232b

P. Stilbs, Automated CORE, RECORD, and GRECORD processing of multi-component PGSE NMR diffusometry data, European Biophysics Journal, vol.191, issue.1, pp.25-32, 2013.
DOI : 10.1007/s00249-012-0794-8

P. Stilbs, K. Paulsen, and P. C. Griffiths, Global Least-Squares Analysis of Large, Correlated Spectral Data Sets:?? Application to Component-Resolved FT-PGSE NMR Spectroscopy, The Journal of Physical Chemistry, vol.100, issue.20, pp.8180-8189, 1996.
DOI : 10.1021/jp9535607

P. Stilbs, RECORD processing ??? A robust pathway to component-resolved HR-PGSE NMR diffusometry, Journal of Magnetic Resonance, vol.207, issue.2, pp.332-336, 2010.
DOI : 10.1016/j.jmr.2010.09.019

M. A. Delsuc and T. E. Malliavin, Maximum Entropy Processing of DOSY NMR Spectra, Analytical Chemistry, vol.70, issue.10, pp.2146-2148, 1998.
DOI : 10.1021/ac9800715

M. Nilsson and G. A. Morris, Speedy Component Resolution: An Improved Tool for Processing Diffusion-Ordered Spectroscopy Data, Analytical Chemistry, vol.80, issue.10, pp.3777-3782, 2008.
DOI : 10.1021/ac7025833

M. Nilsson, The DOSY Toolbox: A new tool for processing PFG NMR diffusion data, Journal of Magnetic Resonance, vol.200, issue.2, pp.296-302, 2009.
DOI : 10.1016/j.jmr.2009.07.022

A. A. Colbourne, G. A. Morris, and M. Nilsson, Local Covariance Order Diffusion-Ordered Spectroscopy: A Powerful Tool for Mixture Analysis, Journal of the American Chemical Society, vol.133, issue.20, pp.7640-7643, 2011.
DOI : 10.1021/ja2004895

R. M. Maria, T. B. Moraes, C. J. Magon, T. Venancio, W. F. Altei et al., Processing of high resolution magic angle spinning spectra of breast cancer cells by the filter diagonalization method, The Analyst, vol.112, issue.19, pp.4546-4551, 2012.
DOI : 10.1039/c2an35451a

Y. Nishiyama, M. H. Frey, S. Mukasa, and H. Utsumi, 13C solid-state NMR chromatography by magic angle spinning 1H T1 relaxation ordered spectroscopy, Journal of Magnetic Resonance, vol.202, issue.2, pp.135-139, 2010.
DOI : 10.1016/j.jmr.2009.10.009

J. F. Cardoso, Blind signal separation: statistical principles, Proceedings of the IEEE, pp.2009-2025, 1998.
DOI : 10.1109/5.720250

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.7237

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

D. Nuzillard, S. Bourg, and J. Nuzillard, Model-Free Analysis of Mixtures by NMR Using Blind Source Separation, Journal of Magnetic Resonance, vol.133, issue.2, pp.358-363, 1998.
DOI : 10.1006/jmre.1998.1481

M. Zibulevsky and B. A. Pearlmutter, Blind Source Separation by Sparse Decomposition in a Signal Dictionary, Neural Computation, vol.1, issue.4, pp.863-882, 1999.
DOI : 10.1016/S0042-6989(97)00169-7

W. Windig and B. Antalek, Direct exponential curve resolution algorithm (DECRA): A novel application of the generalized rank annihilation method for a single spectral mixture data set with exponentially decaying contribution profiles, Chemometrics and Intelligent Laboratory Systems, vol.37, issue.2, pp.241-254, 1997.
DOI : 10.1016/S0169-7439(97)00028-2

B. Antalek and W. Windig, Generalized Rank Annihilation Method Applied to a Single Multicomponent Pulsed Gradient Spin Echo NMR Data Set, Journal of the American Chemical Society, vol.118, issue.42, pp.10331-10332, 1996.
DOI : 10.1021/ja962172v

G. S. Armstrong, N. M. Loening, J. E. Curtis, A. Shaka, and V. A. Mandelshtam, Processing DOSY spectra using the regularized resolvent transform, Journal of Magnetic Resonance, vol.163, issue.1, pp.139-148, 2003.
DOI : 10.1016/S1090-7807(03)00126-5

E. O. Stejskal and J. E. Tanner, Spin Diffusion Measurements: Spin Echoes in the Presence of a Time???Dependent Field Gradient, The Journal of Chemical Physics, vol.42, issue.1, pp.288-292, 1965.
DOI : 10.1063/1.1695690

A. Hyvärinen and E. Oja, Independent component analysis: algorithms and applications, Neural Networks, vol.13, issue.4-5, pp.411-430, 2000.
DOI : 10.1016/S0893-6080(00)00026-5

A. Hyvärinen and E. Oja, Handbook of Independent Component Analysis, 2001.

J. Zhong, N. Didonato, and P. G. Hatcher, Independent component analysis applied to diffusion-ordered spectroscopy: separating nuclear magnetic resonance spectra of analytes in mixtures, Journal of Chemometrics, vol.100, issue.20, pp.150-157, 2012.
DOI : 10.1002/cem.2423

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

Z. Koldovsky, P. Tichavsky, and E. Oja, Efficient variant of algorithm fastica for independent component analysis attaining the cramer-RAO lower bound, IEEE/SP 13th Workshop on Statistical Signal Processing, 2005, pp.1265-1277, 2006.
DOI : 10.1109/SSP.2005.1628758

H. Stogbauer, A. Kraskov, S. A. Astakhov, and P. Grassberger, Least-dependent-component analysis based on mutual information, Physical Review E, vol.70, issue.6, 2004.
DOI : 10.1103/PhysRevE.70.066123

S. A. Astakhov, H. Stogbauer, A. Kraskov, and P. Grassberger, Monte Carlo Algorithm for Least Dependent Non-Negative Mixture Decomposition, Analytical Chemistry, vol.78, issue.5, p.601161
DOI : 10.1021/ac051707c

URL : http://arxiv.org/abs/physics/0601161

Y. B. Monakhova, S. A. Astakhov, A. Kraskov, and S. P. Mushtakova, Independent components in spectroscopic analysis of complex mixtures, Chemometrics and Intelligent Laboratory Systems, vol.103, issue.2, 2010.
DOI : 10.1016/j.chemolab.2010.05.023

I. Toumi, B. Torrsani, and S. Caldarelli, Effective Processing of Pulse Field Gradient NMR of Mixtures by Blind Source Separation, Analytical Chemistry, vol.85, issue.23, pp.11344-11351, 2013.
DOI : 10.1021/ac402085x

URL : https://hal.archives-ouvertes.fr/hal-00933934

S. Mallat, A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way, 2008.

I. Kopriva, I. Jeric, and V. Smrecki, Extraction of multiple pure component 1H and 13C NMR spectra from two mixtures: Novel solution obtained by sparse component analysis-based blind decomposition, Analytica Chimica Acta, vol.653, issue.2, pp.143-153, 2009.
DOI : 10.1016/j.aca.2009.09.019

I. Kopriva and I. Jeric, Blind Separation of Analytes in Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry: Sparseness-Based Robust Multicomponent Analysis, Analytical Chemistry, vol.82, issue.5, pp.1911-1920, 2010.
DOI : 10.1021/ac902640y

W. Naanaa and J. Nuzillard, Blind source separation of positive and partially correlated data, Signal Processing, vol.85, issue.9, pp.1711-1722, 2005.
DOI : 10.1016/j.sigpro.2005.03.006

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

Y. Sun, C. Ridge, F. Del-rio, A. J. Shaka, and J. Xin, Postprocessing and sparse blind source separation of positive and partially overlapped data, Signal Process, pp.91-1838, 2011.

Y. Sun and J. Xin, A Recursive Sparse Blind Source Separation Method and Its Application to Correlated Data in NMR Spectroscopy of Biofluids, Journal of Scientific Computing, vol.1, issue.143, pp.733-753, 2012.
DOI : 10.1007/s10915-011-9528-9

Y. Sun and J. Xin, Nonnegative Sparse Blind Source Separation for NMR Spectroscopy by Data Clustering, Model Reduction, and $\ell_1$ Minimization, SIAM Journal on Imaging Sciences, vol.5, issue.3, pp.886-911, 2012.
DOI : 10.1137/110827223

R. Huo, R. Wehrens, J. Duynhoven, and L. Buydens, Assessment of techniques for DOSY NMR data processing, Analytica Chimica Acta, vol.490, issue.1-2, pp.231-251, 2003.
DOI : 10.1016/S0003-2670(03)00752-9

R. Huo, R. Wehrens, and L. M. Buydens, Improved DOSY NMR data processing by data enhancement and combination of multivariate curve resolution with non-linear least square fitting, Journal of Magnetic Resonance, vol.169, issue.2, pp.257-269, 2004.
DOI : 10.1016/j.jmr.2004.04.019

R. Huo, P. R. Van-de-molengraaf, R. J. Wehrens, and L. Buydens, Diagnostic analysis of experimental artefacts in DOSY NMR data by covariance matrix of the residuals, Journal of Magnetic Resonance, vol.172, issue.2, pp.346-358, 2005.
DOI : 10.1016/j.jmr.2004.11.011

R. Huo, R. Wehrens, and L. Buydens, Robust DOSY NMR data analysis, Chemometrics and Intelligent Laboratory Systems, vol.85, issue.1, pp.9-19, 2007.
DOI : 10.1016/j.chemolab.2006.03.004

P. Paatero and U. Tapper, Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values, Environmetrics, vol.18, issue.2, pp.111-126, 1994.
DOI : 10.1002/env.3170050203

C. Lin, Projected Gradient Methods for Nonnegative Matrix Factorization, Neural Computation, vol.5, issue.10, pp.2756-2779, 2007.
DOI : 10.1007/BF01584660

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.308.9135

D. A. Snyder, F. Zhang, S. L. Robinette, L. Bruschweiler-li, and R. Bruschweiler, Non-negative matrix factorization of two-dimensional NMR spectra: Application to complex mixture analysis, The Journal of Chemical Physics, vol.128, issue.5
DOI : 10.1063/1.2816782

D. D. Lee and H. S. Seung, Algorithms for Non-negative Matrix Factorization, Advances in Neural Information Processing Systems, pp.55-556, 1493.

C. Lin, On the Convergence of Multiplicative Update Algorithms for Nonnegative Matrix Factorization, Neural Networks IEEE Transactions on, vol.18, issue.6, pp.1589-1596, 2007.

P. Sajda, S. Du, and L. C. Parra, Recovery of constituent spectra using nonnegative matrix factorization, pp.321-331, 2003.

P. O. Hoyer, Non-negative sparse coding, Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing, pp.557-565, 2002.
DOI : 10.1109/NNSP.2002.1030067

URL : http://arxiv.org/abs/cs/0202009

P. O. Hoyer, Non-negative matrix factorization with sparseness constraints, Journal of Machine Learning Research, vol.5, pp.1457-1469, 2004.

P. O. Hoyer, The NNSC algorithm

R. Bro and P. , Tutorial and applications

C. F. Beckmann and S. M. Smith, Tensorial extensions of independent component analysis for multisubject FMRI analysis, NeuroImage, vol.25, issue.1, pp.294-311, 2005.
DOI : 10.1016/j.neuroimage.2004.10.043

R. A. Harshman, Foundations of the PARAFAC procedure: Models and conditions for an " explanatory " multi-modal factor analysis, UCLA Working Papers in Phonetics, vol.16, issue.84, 1970.

J. Carroll and 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

R. A. Harshman and M. E. Lundy, PARAFAC: Parallel factor analysis, Computational Statistics & Data Analysis, vol.18, issue.1, pp.39-72, 1994.
DOI : 10.1016/0167-9473(94)90132-5

J. Forshed, R. Stolt, H. Idborg, and S. P. Jacobsson, Enhanced multivariate analysis by correlation scaling and fusion of LC/MS and 1H NMR data, Chemometrics and Intelligent Laboratory Systems, vol.85, issue.2, pp.179-185, 2007.
DOI : 10.1016/j.chemolab.2006.06.012

A. Yilmaz, N. Nyberg, and J. Jaroszewski, H NMR Data and Parallel Factor Analysis, Analytical Chemistry, vol.83, issue.21, pp.8278-85, 2011.
DOI : 10.1021/ac202089g

I. Montoliu, F. J. Martin, S. Collino, S. Rezzi, and S. Kochhar, Multivariate modeling strategy for intercompartmental analysis of tissue and plasma 1h nmr spectrotypes, pp.2397-406, 2009.

M. Nilsson, M. Khajeh, A. Botana, M. A. Bernstein, and G. A. Morris, Diffusion NMR and trilinear analysis in the study of reaction kinetics, Chemical Communications, vol.38, issue.10, pp.0-1252, 2009.
DOI : 10.1039/b820813a

M. Nilsson, A. Botana, and G. A. Morris, -Diffusion-Ordered Spectroscopy: Nuclear Magnetic Resonance Mixture Analysis Using Parallel Factor Analysis, Analytical Chemistry, vol.81, issue.19, pp.8119-8125, 2009.
DOI : 10.1021/ac901321w

URL : https://hal.archives-ouvertes.fr/in2p3-00002960

J. Bjorneras, A. Botana, G. A. Morris, and M. Nilsson, Resolving complex mixtures: trilinear diffusion data, Journal of Biomolecular NMR, vol.47, issue.1, pp.1-7, 2013.
DOI : 10.1007/s10858-013-9752-8

R. Bro, N. Viereck, M. Toft, H. Toft, P. I. Hansen et al., Mathematical chromatography solves the cocktail party effect in mixtures using 2D spectra and PARAFAC, TrAC Trends in Analytical Chemistry, vol.29, issue.4, p.281, 2010.
DOI : 10.1016/j.trac.2010.01.008

I. Toumi, Decomposition methods of nmr signal of complex mixtures: Models and applications, 2013.