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
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
Blind separation of auditory event-related brain responses into independentcomponents, Proceedings of the National Academy of Sciences, vol.94, issue.20, pp.10-979, 1997. ,
A method for making group inferences from functional MRI data using independent component analysis, Human Brain Mapping, vol.2, issue.3, pp.140-151, 2001. ,
DOI : 10.1002/hbm.1048
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.467.1625
Probabilistic Independent Component Analysis for Functional Magnetic Resonance Imaging, IEEE Transactions on Medical Imaging, vol.23, issue.2, pp.137-152, 2004. ,
DOI : 10.1109/TMI.2003.822821
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.62.9887
Independent EEG Sources Are Dipolar, PLoS ONE, vol.16, issue.3, p.30135, 2012. ,
DOI : 10.1371/journal.pone.0030135.t001
URL : https://hal.archives-ouvertes.fr/hal-00674521
Blind source separation and analysis of multispectral astronomical images, Astronomy and Astrophysics Supplement Series, vol.147, issue.1, pp.129-138, 2000. ,
DOI : 10.1051/aas:2000292
All-sky astrophysical component separation with Fast Independent Component Analysis (FASTICA), Monthly Notices of the Royal Astronomical Society, vol.334, issue.1, pp.53-68, 2002. ,
DOI : 10.1046/j.1365-8711.2002.05425.x
URL : http://arxiv.org/abs/astro-ph/0108362
Principal Components and Independent Component Analysis of Solar and Space Data, Solar Physics, vol.327, issue.A5, pp.247-261, 2008. ,
DOI : 10.1016/B978-0-12-498150-8.50024-0
Independent component analysis of Raman spectra: Application on paraffin-embedded skin biopsies, Biomedical Signal Processing and Control, vol.2, issue.1, pp.40-50, 2007. ,
DOI : 10.1016/j.bspc.2007.03.001
Independent Components Analysis with the JADE algorithm, TrAC Trends in Analytical Chemistry, vol.50, pp.22-32, 2013. ,
DOI : 10.1016/j.trac.2013.03.013
URL : https://hal.archives-ouvertes.fr/hal-01349802
Application of independent component analysis to microarrays, Genome Biology, vol.4, issue.11, p.76, 2003. ,
DOI : 10.1186/gb-2003-4-11-r76
Metabolite fingerprinting: detecting biological features by independent component analysis, Bioinformatics, vol.20, issue.15, pp.2447-2454, 2004. ,
DOI : 10.1093/bioinformatics/bth270
URL : http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.321.1933&rep=rep1&type=pdf
Removing electroencephalographic artifacts by blind source separation, Psychophysiology, vol.37, issue.2, pp.163-178, 2000. ,
DOI : 10.1111/1469-8986.3720163
Sparse code shrinkage: Denoising by nonlinear maximum likelihood estimation, Advances in Neural Information Processing Systems, pp.473-479, 1999. ,
Learning Multiscale Sparse Representations for Image and Video Restoration, Multiscale Modeling & Simulation, vol.7, issue.1, pp.214-241, 2008. ,
DOI : 10.1137/070697653
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.105.6238
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
Blind separation of mixture of independent sources through a quasi-maximum likelihood approach, IEEE Transactions on Signal Processing, vol.45, issue.7, pp.1712-1725, 1997. ,
DOI : 10.1109/78.599941
URL : https://hal.archives-ouvertes.fr/hal-01485511
The fixed-point algorithm and maximum likelihood estimation for independent component analysis, Neural Processing Letters, pp.1-5, 1999. ,
Infomax and maximum likelihood for blind source separation, IEEE Signal Processing Letters, vol.4, issue.4, pp.112-114, 1997. ,
DOI : 10.1109/97.566704
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.3619
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
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.297.8229
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
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.110.696
AMICA: An adaptive mixture of independent component analyzers with shared components, 2012. ,
Blind signal separation: statistical principles, Proceedings of the IEEE, vol.86, issue.10, pp.2009-2025, 1998. ,
DOI : 10.1109/5.720250
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.7237
Stability Analysis of Learning Algorithms for Blind Source Separation, Neural Networks, vol.10, issue.8, pp.1345-1351, 1997. ,
DOI : 10.1016/S0893-6080(97)00039-7
Blind source separation with relative newton method, Proc. ICA, pp.897-902, 2003. ,
Newton method for the ICA mixture model, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.1805-1808, 2008. ,
DOI : 10.1109/ICASSP.2008.4517982
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.144.3432
EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis, Journal of Neuroscience Methods, vol.134, issue.1, pp.9-21, 2004. ,
DOI : 10.1016/j.jneumeth.2003.10.009
Caveats with Stochastic Gradient and Maximum Likelihood Based ICA for EEG, International Conference on Latent Variable Analysis and Signal Separation, pp.279-289, 2017. ,
DOI : 10.1007/BF01132771
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
Optimization methods for largescale machine learning, 2016. ,
Variable Metric Method for Minimization, SIAM Journal on Optimization, vol.1, issue.1, pp.1-17, 1991. ,
DOI : 10.1137/0801001
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.693.272
A new approach to variable metric algorithms, The Computer Journal, vol.13, issue.3, pp.317-322, 1970. ,
DOI : 10.1093/comjnl/13.3.317
A Rapidly Convergent Descent Method for Minimization, The Computer Journal, vol.6, issue.2, pp.163-168, 1963. ,
DOI : 10.1093/comjnl/6.2.163
The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations, IMA Journal of Applied Mathematics, vol.6, issue.1, pp.76-90, 1970. ,
DOI : 10.1093/imamat/6.1.76
A family of variable-metric methods derived by variational means, Mathematics of Computation, vol.24, issue.109, pp.23-26, 1970. ,
DOI : 10.1090/S0025-5718-1970-0258249-6
Conditioning of quasi-Newton methods for function minimization, Mathematics of Computation, vol.24, issue.111, pp.647-656, 1970. ,
DOI : 10.1090/S0025-5718-1970-0274029-X
A Limited Memory Algorithm for Bound Constrained Optimization, SIAM Journal on Scientific Computing, vol.16, issue.5, pp.1190-1208, 1995. ,
DOI : 10.1137/0916069
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.6761
Convergence Conditions for Ascent Methods, SIAM Review, vol.11, issue.2, pp.226-235, 1969. ,
DOI : 10.1137/1011036
Line search algorithms with guaranteed sufficient decrease, ACM Transactions on Mathematical Software, vol.20, issue.3, pp.286-307, 1994. ,
DOI : 10.1145/192115.192132
The NumPy Array: A Structure for Efficient Numerical Computation, Computing in Science & Engineering, vol.13, issue.2, pp.22-30, 2011. ,
DOI : 10.1109/MCSE.2011.37
URL : https://hal.archives-ouvertes.fr/inria-00564007
Extended ica removes artifacts from electroencephalographic recordings, Proceedings of the 10th International Conference on Neural Information Processing Systems, ser. NIPS'97, pp.894-900, 1997. ,
Modeling the shape of the scene: A holistic representation of the spatial envelope, International Journal of Computer Vision, vol.42, issue.3, pp.145-175, 2001. ,
DOI : 10.1023/A:1011139631724