C. Gold, D. A. Henze, C. Koch, and G. Buzsáki, On the Origin of the Extracellular Action Potential Waveform: A Modeling Study, Journal of Neurophysiology, vol.95, issue.5, pp.3113-3128, 2006.
DOI : 10.1152/jn.00979.2005

G. Chechik, Spike-Timing-Dependent Plasticity and Relevant Mutual Information Maximization, Neural Computation, vol.395, issue.3, pp.1481-1510, 2003.
DOI : 10.1016/S0896-6273(01)00460-3

C. Rumsey and L. Abbott, Equalization of Synaptic Efficacy by Activity- and Timing-Dependent Synaptic Plasticity, Journal of Neurophysiology, vol.91, issue.5, pp.2273-2280, 2004.
DOI : 10.1152/jn.00900.2003

M. S. Lewicki, A review of methods for spike sorting: the detection and classification of neural action potentials, Network: Computation in Neural Systems, vol.9, issue.4, pp.53-78, 1998.
DOI : 10.1088/0954-898X_9_4_001

M. S. Fee, P. P. Mitra, and D. Kleinfeld, Automatic sorting of multiple unit neuronal signals in the presence of anisotropic and non-Gaussian variability, Journal of Neuroscience Methods, vol.69, issue.2, pp.175-188, 1996.
DOI : 10.1016/S0165-0270(96)00050-7

R. Quian-quiroga, Z. Nadasdy, and Y. Ben, Unsupervised Spike Detection and Sorting with Wavelets and Superparamagnetic Clustering, Neural Computation, vol.84, issue.8, pp.1661-1687, 2004.
DOI : 10.1016/0370-2693(89)91563-3

I. Bankman, K. Johnson, and W. Schneider, Optimal detection, classification, and superposition resolution in neural waveform recordings, IEEE Transactions on Biomedical Engineering, vol.40, issue.8, pp.836-841, 1993.
DOI : 10.1109/10.238472

C. J. De-luca, Physiology and Mathematics of Myoelectric Signals, IEEE Transactions on Biomedical Engineering, vol.26, issue.6, pp.313-325, 1979.
DOI : 10.1109/TBME.1979.326534

A. Holobar and D. Zazula, Multichannel Blind Source Separation Using Convolution Kernel Compensation, IEEE Transactions on Signal Processing, vol.55, issue.9
DOI : 10.1109/TSP.2007.896108

J. J. Kormylo and J. M. , Maximum-Likelihood Seismic Deconvolution, IEEE Transactions on Geoscience and Remote Sensing, vol.21, issue.1, pp.72-82, 1983.
DOI : 10.1109/TGRS.1983.350532

Q. Cheng, R. Chen, and T. Li, Simultaneous wavelet estimation and deconvolution of reflection seismic signals, IEEE Transactions on Geoscience and Remote Sensing, vol.34, issue.2, pp.377-384, 1996.
DOI : 10.1109/36.485115

F. Champagnat, Y. Goussard, and J. Idier, Unsupervised deconvolution of sparse spike trains using stochastic approximation, IEEE Transactions on Signal Processing, vol.44, issue.12, pp.2988-2998, 1996.
DOI : 10.1109/78.553473

S. Bourguignon and H. Carfantan, Bernoulli-gaussian spectral analysis of unevenly spaced astrophysical data, IEEE/SP 13th Workshop on Statistical Signal Processing, 2005, pp.811-816, 2005.
DOI : 10.1109/SSP.2005.1628705

K. C. Mcgill, Z. C. Lateva, and H. R. Marateb, EMGLAB: An interactive EMG decomposition program, Journal of Neuroscience Methods, vol.149, issue.2, pp.121-133, 2005.
DOI : 10.1016/j.jneumeth.2005.05.015

G. Kail, C. Novak, B. Hofer, F. Hlawatsch, and R. O. , Blind Monte Carlo detection-estimation method for optical coherence tomography, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.493-496, 2009.
DOI : 10.1109/ICASSP.2009.4959628

D. Ge, E. L. Carpentier, and D. Farina, Unsupervised Bayesian Decomposition of Multi-Unit EMG Recordings using Tabu Search, IEEE Trans. Biomed Eng, vol.57, issue.3, pp.561-517, 2010.

D. Farina and D. Falla, Effect of muscle-fiber velocity recovery function on motor unit action potential properties in voluntary contractions, Muscle and nerve, pp.650-658, 2008.
DOI : 10.1002/mus.20948

K. C. Mcgill, Optimal resolution of superimposed action potentials, IEEE Transactions on Biomedical Engineering, vol.49, issue.7, pp.640-650, 2002.
DOI : 10.1109/TBME.2002.1010847

E. H. Hollander and G. A. Orban, Spike Recognition and On-Line Classification by Unsupervised Learning System, IEEE Trans. Biomed Eng. BME, vol.26, issue.5, pp.279-284, 1979.

M. S. Lewicki, Bayesian Modeling and Classification of Neural Signals, Neural Computation, vol.12, issue.5, pp.1005-1030, 1994.
DOI : 10.1109/78.120795

R. Chandra and L. Optican, Detection, classification, and superposition resolution of action potentials in multiunit single-channel recordings by an on-line real-time neural network, IEEE Transactions on Biomedical Engineering, vol.44, issue.5, pp.403-412, 1997.
DOI : 10.1109/10.568916

F. A. Atiya, Recognition of multiunit neural signals, IEEE Transactions on Biomedical Engineering, vol.39, issue.7, pp.723-729, 1992.
DOI : 10.1109/10.142647

S. Takahashi, Y. Anzai, and Y. Sakurai, Automatic Sorting for Multi-Neuronal Activity Recorded With Tetrodes in the Presence of Overlapping Spikes, Journal of Neurophysiology, vol.89, issue.4, pp.2245-2258, 2003.
DOI : 10.1152/jn.00827.2002

S. Takahashi and Y. Sakurai, Real-time and automatic sorting of multi-neuronal activity for sub-millisecond interactions in vivo, Neuroscience, vol.134, issue.1, pp.301-315, 2005.
DOI : 10.1016/j.neuroscience.2005.03.031

S. Takahashi, Y. Sakurai, M. Tsukada, and Y. Anzai, Classification of neuronal activities from tetrode recordings using independent component analysis, Neurocomputing, vol.49, issue.1-4, pp.289-298, 2002.
DOI : 10.1016/S0925-2312(02)00528-3

A. Holobar and D. Zazula, Correlation-based decomposition of surface electromyograms at low contraction forces, Medical & Biological Engineering & Computing, vol.51, issue.6, pp.487-495, 2004.
DOI : 10.1007/BF02350989

A. Holobar, D. Farina, M. Gazzonib, R. Merlettib, and D. Zazula, Estimating motor unit discharge patterns from high-density surface electromyogram, Clinical Neurophysiology, vol.120, issue.3, pp.551-562, 2009.
DOI : 10.1016/j.clinph.2008.10.160

R. Lefever and C. De-luca, A Procedure for Decomposing the Myoelectric Signal Into Its Constituent Action Potentials - Part I: Technique, Theory, and Implementation, IEEE Transactions on Biomedical Engineering, vol.29, issue.3, pp.149-157, 1982.
DOI : 10.1109/TBME.1982.324881

K. C. Mcgill, K. L. Cummins, and L. J. Dorfman, Automatic Decomposition of the Clinical Electromyogram, IEEE Transactions on Biomedical Engineering, vol.32, issue.7, pp.470-477, 1985.
DOI : 10.1109/TBME.1985.325562

K. C. Mcgill and L. J. Dorfman, High-Resolution Alignment of Sampled Waveforms, IEEE Transactions on Biomedical Engineering, vol.31, issue.6, pp.462-468, 1984.
DOI : 10.1109/TBME.1984.325413

F. Wood and M. J. Black, A nonparametric Bayesian alternative to spike sorting, Journal of Neuroscience Methods, vol.173, issue.1, pp.1-12, 2008.
DOI : 10.1016/j.jneumeth.2008.04.030

D. Ge, Déconvolution impulsionnelle multi-source. Application aux signaux électromyographiques, 2009.

P. J. Green, Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrika, vol.82, issue.4, pp.711-732, 1995.
DOI : 10.1093/biomet/82.4.711

C. P. Robert and G. Casella, Monte Carlo Statistical Methods, Springer Texts in Statistics, 2004.

L. Tierney, Markov Chains for Exploring Posterior Distributions, The Annals of Statistics, vol.22, issue.4, pp.1701-1728, 1994.
DOI : 10.1214/aos/1176325750

C. J. Luca, A. Adam, R. Wotiz, L. D. Gilmore, and S. H. Nawab, Decomposition of Surface EMG Signals, Journal of Neurophysiology, vol.96, issue.3, pp.1646-1657, 2006.
DOI : 10.1152/jn.00009.2006

C. T. Moritz, B. K. Barry, M. A. Pascoe, and R. M. Enoka, Discharge Rate Variability Influences the Variation in Force Fluctuations Across the Working Range of a Hand Muscle, Journal of Neurophysiology, vol.93, issue.5, pp.2449-2459, 2004.
DOI : 10.1152/jn.01122.2004

A. J. Fuglevand, D. A. Winter, and A. E. Patla, Models of recruitment and rate coding organization in motor-unit pools, J. Neurophysiol, vol.70, issue.6, pp.2470-2488, 1993.