S. A. Abdallah and M. D. Plumbley, If edges are the independent components of natural images, what are the independent components of natural sounds, Proc

F. Abrard and Y. Deville, A time???frequency blind signal separation method applicable to underdetermined mixtures of dependent sources, Signal Processing, vol.85, issue.7, pp.1389-1403, 2005.
DOI : 10.1016/j.sigpro.2005.02.010

F. Abrard, Y. Deville, and P. White, From blind source separation to blind source cancellation in the underdetermined case : a new approach based on time-frequency analysis, Proc. Int. Workshop on Independent Component Analysis and Blind Signal Separation, 2001.

M. Aharon, M. Elad, and A. M. Bruckstein, On the uniqueness of overcomplete dictionaries, and a practical way to retrieve them, Linear Algebra and its Applications, vol.416, issue.1, pp.48-67, 2006.
DOI : 10.1016/j.laa.2005.06.035

A. Aïssa-el-bey, K. Abed-meraim, and Y. Grenier, Underdetermined blind source separation of audio sources in time-frequency domain, Proc. First Workshop on Signal Processing with Sparse/Structured Representations (SPARS'05), 2005.

S. Arberet, R. Gribonval, and F. Bimbot, A Robust Method to Count and Locate Audio Sources in a Stereophonic Linear Instantaneous Mixture, Proc. of the Int'l. Workshop on Independent Component Analysis and Blind Signal Separation, pp.536-543, 2006.
DOI : 10.1007/11679363_67
URL : https://hal.archives-ouvertes.fr/inria-00544925

S. Arberet, R. Gribonval, and F. Bimbot, A Robust Method to Count and Locate Audio Sources in a Stereophonic Linear Anechoic Mixture, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07, 2007.
DOI : 10.1109/ICASSP.2007.366787
URL : https://hal.archives-ouvertes.fr/inria-00544778

R. Balan, J. Rosca-duarte, S. Sarvotham, M. B. Wakin, and R. G. Baraniuk, Statistical properties of STFT ratios for two channel systems and applications to blind source separation An information-theoretic approach to distributed compressed sensing, Proc. Int. Workshop on Independent Component Analysis and Blind Signal Separation Proc. 45rd Conference on Communication, Control, and Computing, pp.429-434, 2000.

L. Benaroya, Séparation de plusieurs sources sonores avec un seul microphone, 2003.

L. Benaroya and F. Bimbot, Wiener-based source separation with HMM/GMM using a single sensor, Proc. 4th Int. Symp. on Independent Component Anal. and Blind Signal Separation (ICA2003), 2003.

L. Benaroya, F. Bimbot, and R. Gribonval, Audio source separation with a single sensor, IEEE Transactions on Audio, Speech and Language Processing, vol.14, issue.1, pp.191-199, 2006.
DOI : 10.1109/TSA.2005.854110
URL : https://hal.archives-ouvertes.fr/inria-00544949

L. Benaroya, R. Gribonval, and F. Bimbot, Représentations parcimonieuses pour la séparation de sources avec un seul capteur, GRETSI 2001, 2001.

L. Benaroya, L. Mcdonagh, F. Bimbot, and R. Gribonval, Non negative sparse representation for Wiener based source separation with a single sensor, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., p.613, 2003.
DOI : 10.1109/ICASSP.2003.1201756
URL : https://hal.archives-ouvertes.fr/inria-00574784

C. Bennett and R. Sharpley, Interpolation of operators, 1988.

J. Bergh and J. Löfström, Interpolation Spaces, an introduction. Number 223 in Comprehensive Studies in Mathematics, 1976.

D. Bertsekas, Non-Linear Programming, Athena Scientific, 1995.

J. Bobin, Y. Moudden, J. Starck, and M. Elad, Multichannel morphological component analysis, Proc. First Workshop on Signal Processing with Sparse/Structured Representations (SPARS'05), 2005.

P. Bofill and M. Zibulevsky, Underdetermined blind source separation using sparse representations, Signal Processing, vol.81, issue.11, pp.2353-2362, 2001.
DOI : 10.1016/S0165-1684(01)00120-7
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.3694

L. Borup, R. Gribonval, and M. Nielsen, Bi-framelet systems with few vanishing moments characterize Besov spaces, Applied and Computational Harmonic Analysis, vol.17, issue.1, pp.3-28, 2004.
DOI : 10.1016/j.acha.2004.01.004
URL : https://hal.archives-ouvertes.fr/inria-00567265

L. Borup, R. Gribonval, and M. Nielsen, Tight wavelet frames in Lebesgue and Sobolev spaces, Journal of Function Spaces and Applications, vol.2, issue.3, pp.227-252, 2004.
DOI : 10.1155/2004/792493
URL : https://hal.archives-ouvertes.fr/inria-00567343

L. Borup, R. Gribonval, and M. Nielsen, Beyond coherence: Recovering structured time???frequency representations, Applied and Computational Harmonic Analysis, vol.24, issue.1, 2007.
DOI : 10.1016/j.acha.2007.09.002
URL : https://hal.archives-ouvertes.fr/inria-00544766

R. Gribonval, C. Févotte, and E. Vincent, BSS_EVAL toolbox user guide ? revision 2.0, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00564760

E. J. Candès, J. Romberg, and T. Tao, Stable signal recovery from incomplete and inaccurate measurements, Communications on Pure and Applied Mathematics, vol.7, issue.8, pp.1207-1223, 2006.
DOI : 10.1002/cpa.20124

J. Cardoso, 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

J. Chen and X. Huo, Theoretical Results on Sparse Representations of Multiple-Measurement Vectors, IEEE Transactions on Signal Processing, vol.54, issue.12, pp.4634-4643, 2006.
DOI : 10.1109/TSP.2006.881263

S. Chen, D. L. Donoho, and M. A. Saunders, Atomic Decomposition by Basis Pursuit, SIAM Journal on Scientific Computing, vol.20, issue.1, pp.33-61, 1999.
DOI : 10.1137/S1064827596304010
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.113.7694

O. Christensen, An introduction to frames and Riesz bases, Birkhauser, 2003.

S. F. Cotter, B. Rao, K. Engan, and K. Kreutz-delgado, Sparse solutions to linear inverse problems with multiple measurement vectors, IEEE Transactions on Signal Processing, vol.53, issue.7, pp.2477-2488, 2005.
DOI : 10.1109/TSP.2005.849172

I. Daubechies, M. Defrise, and C. Mol, An iterative thresholding algorithm for linear inverse problems with a sparsity constraint, Communications on Pure and Applied Mathematics, vol.58, issue.11, pp.1413-1457, 2004.
DOI : 10.1002/cpa.20042

L. Daudet and B. Torrésani, Hybrid representations for audiophonic signal encoding . Signal Processing, special issue on Image and Video Coding Beyond Standards, pp.1595-1617, 2002.
URL : https://hal.archives-ouvertes.fr/hal-01300317

M. E. Davies and N. Mitianoudis, Simple mixture model for sparse overcomplete ICA, IEE Proceedings -Vision Image and Signal Processing special issue on Nonlinear and Non-Gaussian Signal Processing, pp.35-43, 2004.
DOI : 10.1049/ip-vis:20040304

G. Davis, S. Mallat, and M. Avellaneda, Adaptive greedy approximations, Constructive Approximation, vol.21, issue.1, pp.57-98, 1997.
DOI : 10.1007/BF02678430
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.47.7530

R. A. Devore and V. N. Temlyakov, Some remarks on greedy algorithms, Advances in Computational Mathematics, vol.102, issue.1, pp.173-187, 1996.
DOI : 10.1007/BF02124742

A. Ronald, G. G. Devore, and . Lorentz, Constructive approximation, 1993.

S. J. Dilworth, D. Kutzurova, N. J. Kalton, and V. Temlyakov, The Thresholding Greedy Algorithm, Greedy Bases, and Duality, Constructive Approximation, vol.19, issue.4, pp.575-597, 2003.
DOI : 10.1007/s00365-002-0525-y

D. Donoho, M. Elad, and V. Temlyakov, Stable recovery of sparse overcomplete representations in the presence of noise, IEEE Transactions on Information Theory, vol.52, issue.1, pp.6-18, 2006.
DOI : 10.1109/TIT.2005.860430

L. David and . Donoho, Compressed sensing, IEEE Trans. Inform. Theory, vol.52, issue.4, pp.1289-1306, 2006.

D. L. Donoho and M. Elad, Optimally sparse representation in general (nonorthogonal) dictionaries via ??1 minimization, Proceedings of the National Academy of Sciences, vol.100, issue.5, pp.2197-2202, 2003.
DOI : 10.1073/pnas.0437847100

D. L. Donoho and X. Huo, Uncertainty principles and ideal atomic decomposition, IEEE Transactions on Information Theory, vol.47, issue.7, pp.472845-2862, 2001.
DOI : 10.1109/18.959265
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.9300

D. L. Donoho and I. M. Johnstone, Ideal denoising in an orthonormal basis chosen from a library of bases, 43] C. Dossal. Estimation de fonctions géométriques et déconvolution, pp.1317-1322, 1994.

S. Dubnov and N. Tishby, Influence of frequency modulating jitter on higher order moments of sound residual with applications to synthesis and classification, Proc. Int. Computer Music Conf. (ICMC'96), page 378 385, Hong-Kong, 1996. [45] EBU. SQAM -Sound Quality Assessment Material

B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani, Least angle regression, Annals of Statistics, vol.32, issue.2, pp.407-499, 2004.

M. Elad, Shrinkage for redundant representations, Proc. SPARS'05, 2005.
DOI : 10.1109/cvpr.2006.143
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.108.3046

M. Elad, Why simple shrinkage is still relevant for redundant representations ? Technical report, The Technion -Israel Institute of Technology, 2005.

M. Elad and A. M. Bruckstein, A generalized uncertainty principle and sparse representation in pairs of bases, IEEE Transactions on Information Theory, vol.48, issue.9, pp.2558-2567, 2002.
DOI : 10.1109/TIT.2002.801410

F. Deville and . Abrard, Blind separation of dependent sources using the " timefrequency ratio of mixtures " approach, ISSPA 2003, 2003.

A. Feuer and A. Nemirovsky, On sparse representation in pairs of bases, IEEE Transactions on Information Theory, vol.49, issue.6, pp.1579-1581, 2003.
DOI : 10.1109/TIT.2003.811926

C. Févotte and C. Doncarli, Two Contributions to Blind Source Separation Using Time???Frequency Distributions, IEEE Signal Processing Letters, vol.11, issue.3, pp.386-389, 2004.
DOI : 10.1109/LSP.2003.819343

C. Févotte and S. J. , A Bayesian Approach for Blind Separation of Sparse Sources, IEEE Transactions on Audio, Speech and Language Processing, vol.14, issue.6, pp.2174-2188, 2006.
DOI : 10.1109/TSA.2005.858523

D. J. Field and B. A. Olshausen, Emergence of simple-cell receptive field properties by learning a sparse code for natural images, Nature, vol.381, pp.607-609, 1996.

M. A. Figueiredo and R. D. Nowak, An EM algorithm for wavelet-based image restoration, IEEE Transactions on Image Processing, vol.12, issue.8, pp.906-916, 2003.
DOI : 10.1109/TIP.2003.814255

P. Vandergheynst, . Figueras, R. Ventura, and P. Frossard, Low rate and flexible image coding with redundant representations, IEEE Transactions on Image Processing, vol.15, issue.3, pp.726-739, 2006.

M. Fornasier and H. Rauhut, Recovery Algorithms for Vector-Valued Data with Joint Sparsity Constraints, SIAM Journal on Numerical Analysis, vol.46, issue.2, 2006.
DOI : 10.1137/0606668909

B. Fox, A. Sabin, B. Pardo, and A. Zopf, Modeling Perceptual Similarity of Audio Signals for Blind Source Separation Evaluation, Independent Component Analysis and Signal Separation, pp.454-461, 2007.
DOI : 10.1007/978-3-540-74494-8_57

J. Fuchs, Extension of the Pisarenko method to sparse linear arrays, 1995 International Conference on Acoustics, Speech, and Signal Processing, pp.2100-2103, 1995.
DOI : 10.1109/ICASSP.1995.478489

J. Fuchs, Linear programming in spectral estimation. Application to array processing, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, pp.3161-3164, 1996.
DOI : 10.1109/ICASSP.1996.550547

J. Fuchs, Extension of the Pisarenko method to sparse linear arrays, 1995 International Conference on Acoustics, Speech, and Signal Processing, pp.2413-2421, 1997.
DOI : 10.1109/ICASSP.1995.478489

J. Fuchs, Multipath time-delay estimation, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.527-530, 1997.
DOI : 10.1109/ICASSP.1997.599691
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.4498

J. Fuchs, Une approche à l'estimation et l'identification simultanées, Actes du seizième colloque GRETSI, pp.1273-1276, 1997.

J. Fuchs, Detection and estimation of superimposed signals, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181), pp.1649-1652, 1998.
DOI : 10.1109/ICASSP.1998.681771

J. Fuchs, Multipath time-delay detection and estimation, IEEE Transactions on Signal Processing, vol.47, issue.1, pp.237-243, 1999.
DOI : 10.1109/78.738263

J. Fuchs, On Sparse Representations in Arbitrary Redundant Bases, IEEE Transactions on Information Theory, vol.50, issue.6, pp.1341-1344, 2004.
DOI : 10.1109/TIT.2004.828141

J. Fuchs, Recovery of Exact Sparse Representations in the Presence of Bounded Noise, IEEE Transactions on Information Theory, vol.51, issue.10, pp.3601-3608, 2005.
DOI : 10.1109/TIT.2005.855614

J. Fuchs, Some further results on the recovery algorithms, Proc. First Workshop on Signal Processing with Sparse/Structured Representations (SPARS'05), pp.67-70, 2005.

A. C. Gilbert, S. Muthukrishnan, M. J. Strauss, and J. Tropp, Improved sparse approximation over quasi-incoherent dictionaries, Int. Conf. on Image Proc. (ICIP'03), pp.37-40, 2003.

F. Girosi, An Equivalence Between Sparse Approximation and Support Vector Machines, Neural Computation, vol.20, issue.6, pp.1455-1480, 1998.
DOI : 10.1007/BF01437407
URL : http://alpha-bits.ai.mit.edu/people/girosi/home-page/Girosi98.pdf

I. F. Gorodnitsky and B. D. Rao, Sparse signal reconstruction from limited data using FOCUSS: a re-weighted minimum norm algorithm, IEEE Transactions on Signal Processing, vol.45, issue.3, pp.600-616, 1997.
DOI : 10.1109/78.558475

]. R. Gribonval, Sparse decomposition of stereo signals with Matching Pursuit and application to blind separation of more than two sources from a stereo mixture, IEEE International Conference on Acoustics Speech and Signal Processing, p.3057, 2002.
DOI : 10.1109/ICASSP.2002.5745294
URL : https://hal.archives-ouvertes.fr/inria-00574786

R. Gribonval and E. Bacry, Harmonic decomposition of audio signals with matching pursuit, IEEE Transactions on Signal Processing, vol.51, issue.1, pp.101-111, 2003.
DOI : 10.1109/TSP.2002.806592
URL : https://hal.archives-ouvertes.fr/inria-00576203

R. Gribonval, L. Benaroya, E. Vincent, and C. Févotte, Proposals for performance measurement in source separation, Proc. 4th Int. Symp. on Independent Component Anal. and Blind Signal Separation (ICA2003), pp.763-768, 2003.
URL : https://hal.archives-ouvertes.fr/inria-00570123

R. Gribonval, R. M. Figueras, P. Ventura, and . Vandergheynst, A simple test to check the optimality of sparse signal approximations, EURASIP Signal Processing, special issue on Sparse Approximations in Signal and Image Processing, pp.496-510, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00564503

R. Gribonval, S. Krstulovi´ckrstulovi´c, and . Mptk, The Matching Pursuit Toolkit, 2005.

R. Gribonval, B. Mailhe, H. Rauhut, K. Schnass, and P. Vandergheynst, Average Case Analysis of Multichannel Thresholding, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07, 2007.
DOI : 10.1109/ICASSP.2007.366370
URL : https://hal.archives-ouvertes.fr/inria-00544776

R. Gribonval and M. Nielsen, Approximate weak greedy algorithms, Advances in Computational Mathematics, vol.14, issue.4, pp.361-378, 2001.
DOI : 10.1023/A:1012255021470
URL : https://hal.archives-ouvertes.fr/inria-00576643

R. Gribonval and M. Nielsen, Some remarks on nonlinear approximation with Schauder bases, East J. Approx, vol.7, issue.3, pp.267-285, 2001.
URL : https://hal.archives-ouvertes.fr/inria-00576640

R. Gribonval and M. Nielsen, Nonlinear Approximation with Dictionaries. II. Inverse Estimates, Constructive Approximation, vol.24, issue.2, 2002.
DOI : 10.1007/s00365-005-0621-x
URL : https://hal.archives-ouvertes.fr/inria-00564480

R. Gribonval and M. Nielsen, Approximation with highly redundant dictionaries, Wavelets: Applications in Signal and Image Processing X
DOI : 10.1117/12.504776
URL : https://hal.archives-ouvertes.fr/inria-00576208

R. Gribonval and M. Nielsen, Highly sparse representations from dictionaries are unique and independent of the sparseness measure, Applied and Computational Harmonic Analysis, vol.22, issue.3, 2003.
DOI : 10.1016/j.acha.2006.09.003
URL : https://hal.archives-ouvertes.fr/inria-00544779

R. Gribonval and M. Nielsen, Sparse representations in unions of bases, IEEE Transactions on Information Theory, vol.49, issue.12, pp.3320-3325, 2003.
DOI : 10.1109/TIT.2003.820031
URL : https://hal.archives-ouvertes.fr/inria-00570057

R. Gribonval and M. Nielsen, Nonlinear Approximation with Dictionaries I. Direct Estimates, Journal of Fourier Analysis and Applications, vol.10, issue.1, pp.51-71, 2004.
DOI : 10.1007/s00041-004-8003-5
URL : https://hal.archives-ouvertes.fr/inria-00567266

R. Gribonval and M. Nielsen, On a Problem of Gr???chenig About Nonlinear Approximation with Localized Frames, Journal of Fourier Analysis and Applications, vol.10, issue.4, pp.433-437, 2004.
DOI : 10.1007/s00041-004-3072-z

R. Gribonval and M. Nielsen, On approximation with spline generated framelets, Constr. Approx, vol.20, issue.2, pp.207-232, 2004.
URL : https://hal.archives-ouvertes.fr/inria-00567338

R. Gribonval and M. Nielsen, On the strong uniqueness of highly sparse expansions from redundant dictionaries, Proc. Int Conf. Independent Component Analysis (ICA'04), 2004.
URL : https://hal.archives-ouvertes.fr/inria-00567341

R. Gribonval and M. Nielsen, Beyond sparsity: Recovering structured representations by ${\ell}^1$ minimization and greedy algorithms, Advances in Computational Mathematics, vol.49, issue.6, 2006.
DOI : 10.1007/s10444-005-9009-5
URL : https://hal.archives-ouvertes.fr/inria-00544767

R. Gribonval and P. Vandergheynst, On the exponential convergence of matching pursuits in quasi-incoherent dictionaries, IEEE Transactions on Information Theory, vol.52, issue.1, pp.255-261, 2006.
DOI : 10.1109/TIT.2005.860474
URL : https://hal.archives-ouvertes.fr/inria-00544945

R. Gribonval, H. Rauhut, K. Schnass, and P. Vandergheynst, Atoms of All Channels, Unite! Average Case Analysis of??Multi-Channel Sparse Recovery Using Greedy Algorithms, Journal of Fourier Analysis and Applications, vol.86, issue.3, 2007.
DOI : 10.1007/s00041-008-9044-y
URL : https://hal.archives-ouvertes.fr/inria-00146660

K. Gröchenig, Localized frames are finite unions of riesz sequences, Advances in Computational Mathematics, vol.18, issue.2/4, pp.149-157, 2003.
DOI : 10.1023/A:1021368609918

K. Gröchenig, Localization of Frames, Banach Frames, and the Invertibility of the Frame Operator, Journal of Fourier Analysis and Applications, vol.10, issue.2, pp.105-132, 2004.
DOI : 10.1007/s00041-004-8007-1

K. Gröchenig and E. Cordero, Localization of frames II, Appl. Comp. Harm. Anal, 2004.

R. Qing and J. , A Bernstein-type inequality associated with wavelet decomposition, Constr. Approx, vol.9, issue.2-3, pp.299-318, 1993.

P. Jost, P. Vandergheynst, S. Lesage, and R. Gribonval, MoTIF: An Efficient Algorithm for Learning Translation Invariant Dictionaries, 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006.
DOI : 10.1109/ICASSP.2006.1661411
URL : https://hal.archives-ouvertes.fr/inria-00544911

A. Jourjine, S. Rickard, and O. Yilmaz, Blind separation of disjoint orthogonal signals: demixing N sources from 2 mixtures, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), pp.2985-2988, 2000.
DOI : 10.1109/ICASSP.2000.861162

G. Kerkyacharian and D. Picard, Entropy, Universal Coding, Approximation, and Bases Properties, Constructive Approximation, vol.20, issue.1, 2001.
DOI : 10.1007/s00365-003-0556-z
URL : https://hal.archives-ouvertes.fr/hal-00102265

K. Kreutz-delgado, B. D. Rao, K. Engan, T. Lee, and T. J. Sejnowski, Convex/schur-convex (csc) log-priors and sparse coding, 6th Joint Symposium on Neural Computation, pp.65-71, 1999.

S. Krstulovic and R. Gribonval, Mptk: Matching Pursuit Made Tractable, 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, pp.496-499, 2006.
DOI : 10.1109/ICASSP.2006.1660699
URL : https://hal.archives-ouvertes.fr/inria-00544919

T. Lee, M. S. Lewicki, M. Girolami, and T. J. Sejnowski, Blind source separation of more sources than mixtures using overcomplete representations, IEEE Signal Processing Letters, vol.6, issue.4, pp.87-90, 1999.

]. S. Lesage, Apprentissage de dictionnaires structurés pour la modélisation parcimonieuse des signaux multicanaux, 2007.

S. Lesage, R. Gribonval, F. Bimbot, and L. Benaroya, Learning Unions of Orthonormal Bases with Thresholded Singular Value Decomposition, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., pp.293-296, 2005.
DOI : 10.1109/ICASSP.2005.1416298
URL : https://hal.archives-ouvertes.fr/inria-00564483

S. Lesage, S. Krstulovic, and R. Gribonval, Séparation de sources dans le cas sousdéterminé : comparaison de deux approches basées sur des décompositions parcimonieuses, Proc. 20ème colloque GRETSI sur le traitement du signal et des images, 2005.

S. Lesage, S. Krstulovic, and R. Gribonval, Under-Determined Source Separation: Comparison of Two Approaches Based on Sparse Decompositions, Proc. of the Int'l. Workshop on Independent Component Analysis and Blind Signal Separation, pp.633-640, 2006.
DOI : 10.1007/11679363_79
URL : https://hal.archives-ouvertes.fr/inria-00544929

D. Leviatan and V. N. Temlyakov, Simultaneous approximation by greedy algorithms, Advances in Computational Mathematics, vol.107, issue.1-3, 2003.
DOI : 10.1007/s10444-004-7613-4
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.377.936

M. S. Lewicki, Efficient coding of natural sounds, Nature Neuroscience, vol.5, issue.4, pp.356-363, 2002.
DOI : 10.1038/nn831

M. S. Lewicki and T. J. Sejnowski, Learning Overcomplete Representations, Neural Computation, vol.33, issue.2, pp.337-365, 2000.
DOI : 10.1109/18.119725

J. Lin, D. Grier, and J. Cowan, Faithful Representation of Separable Distributions, Neural Computation, vol.1, issue.6, pp.1305-1320, 1997.
DOI : 10.1007/BF00320480

D. M. Malioutov, M. Cetin, and A. S. Willsky, Homotopy continuation for sparse signal representation, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., pp.733-736, 2005.
DOI : 10.1109/ICASSP.2005.1416408
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.61.5573

S. Mallat, A Wavelet Tour of Signal Processing, 1998.

S. Mallat and Z. Zhang, Matching pursuits with time-frequency dictionaries, IEEE Transactions on Signal Processing, vol.41, issue.12, pp.3397-3415, 1993.
DOI : 10.1109/78.258082
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.335.5769

T. Melia and S. Rickard, Extending the DUET blind source separation technique, Proc. First Workshop on Signal Processing with Sparse/Structured Representations (SPARS'05), pp.67-70, 2005.

G. Monaci, P. Jost, P. Vandergheynst, B. Mailhe, S. Lesage et al., Learning Multi-modal Dictionaries: Application to Audiovisual Data, Proc. of International Workshop on Multimedia Content Representation, Classification and Security (MCRCS'06), pp.538-545, 2006.
DOI : 10.1007/11848035_71
URL : https://hal.archives-ouvertes.fr/inria-00544773

G. Monaci, P. Jost, P. Vandergheynst, B. Mailhe, S. Lesage et al., Learning Multimodal Dictionaries, IEEE Transactions on Image Processing, vol.16, issue.9, pp.2272-2283, 2007.
DOI : 10.1109/TIP.2007.901813
URL : https://hal.archives-ouvertes.fr/inria-00544772

B. Natarajan, Sparse Approximate Solutions to Linear Systems, SIAM Journal on Computing, vol.24, issue.2, pp.227-234, 1995.
DOI : 10.1137/S0097539792240406

A. Ozerov, Adaptation de modèles statistiques pour la séparation de sources monocapteur Application à la séparation voix / musique dans les chansons, 2006.

A. Ozerov, R. Gribonval, P. Philippe, and F. Bimbot, Séparation voix / musique à partir d'enregistrements mono : quelques remarques sur le choix et l'adaptation des modèles, Proc. 20ème colloque GRETSI sur le traitement du signal et des images, 2005.

A. Ozerov, P. Philippe, R. Gribonval, and F. Bimbot, One microphone singing voice separation using source-adapted models, IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2005., pp.90-93, 2005.
DOI : 10.1109/ASPAA.2005.1540176
URL : https://hal.archives-ouvertes.fr/inria-00564491

Y. C. Pati, R. Rezaiifar, and P. S. Krishnaprasad, Orthonormal matching pursuit : recursive function approximation with applications to wavelet decomposition, Proceedings of the 27 th Annual Asilomar Conf. on Signals, Systems and Computers, 1993.

E. Pearson, The Multiresolution Fourier Transform and its application to Polyphonic Audio Analysis, 1991.

L. Granai, L. Peotta, and P. Vandergheynst, Image compression using an edge adapted redundant dictionary and wavelets, Signal Processing, vol.86, issue.3, pp.444-456, 2006.

M. Plumbley, Geometry and homotopy for ? 1 sparse signal representations, Proc. First Workshop on Signal Processing with Sparse/Structured Representations (SPARS'05), pp.67-70, 2005.

J. P. Princen and A. B. Bradley, Analysis/synthesis filter bank design bases on time domain aliasing cancellation, IEEE Trans. Acoustics, Speech and Signal Proc. ASSP, issue.5, pp.341153-1161, 1986.

M. Puigt and Y. Deville, Time???frequency ratio-based blind separation methods for attenuated and time-delayed sources, Mechanical Systems and Signal Processing, vol.19, issue.6, pp.1348-1379, 2005.
DOI : 10.1016/j.ymssp.2005.08.003
URL : https://hal.archives-ouvertes.fr/hal-00270877

L. R. Rabiner and R. W. Schafer, Digital Processing of Speech Signals, 1978.

P. Vandergheynst, A. Rahmoune, and P. Frossard, Flexible motion-adaptive video coding with redundant expansions, IEEE Transactions on Circuits and Systems for Video Technology, pp.178-190, 2006.

S. Rickard, R. Balan, and J. Rosca, Real-time time-frequency based blind source separation, 3rd International Conference on Independent Component Analysis and Blind Source Separation (ICA2001), 2001.

B. Rivet, L. Girin, and C. Jutten, Mixing Audiovisual Speech Processing and Blind Source Separation for the Extraction of Speech Signals From Convolutive Mixtures, IEEE Transactions on Audio, Speech and Language Processing, vol.15, issue.1, pp.96-108, 2007.
DOI : 10.1109/TASL.2006.872619
URL : https://hal.archives-ouvertes.fr/hal-00174100

M. Rudelson and R. Vershynin, Sparse reconstruction by convex relaxation: Fourier and Gaussian measurements, 2006 40th Annual Conference on Information Sciences and Systems, 2006.
DOI : 10.1109/CISS.2006.286463
URL : http://arxiv.org/abs/math/0602559

R. Saab, Ö. Yilmaz, M. J. Mckeown, and R. Abugharbieh, Underdetermined sparse blind source separation with delays, Proc. First Workshop on Signal Processing with Sparse/Structured Representations (SPARS'05), pp.67-70, 2005.

F. Santosa and W. W. Symes, Linear Inversion of Band-Limited Reflection Seismograms, SIAM Journal on Scientific and Statistical Computing, vol.7, issue.4, pp.1307-1330, 1986.
DOI : 10.1137/0907087

A. Shrijver, Theory of Linear and Integer Programming, 1998.

J. L. Starck, E. J. Candès, and D. L. Donoho, The curvelet transform for image denoising, IEEE Transactions on Image Processing, vol.11, issue.6, pp.670-684, 2002.
DOI : 10.1109/TIP.2002.1014998

J. Starck, M. Elad, and D. L. Donoho, Image decomposition: separation of texture from piecewise smooth content, Wavelets: Applications in Signal and Image Processing X, pp.571-582, 2003.
DOI : 10.1117/12.507447

J. Starck, Y. Moudden, J. Bobin, M. Elad, and D. L. Donoho, Morphological component analysis, Wavelets XI, 2005.
DOI : 10.1117/12.615237
URL : https://hal.archives-ouvertes.fr/hal-00090691

S. B. Stechkin, On absolute convergence of orthogonal series, Dok. Akad. Nauk SSSR, vol.102, pp.37-40, 1955.

V. N. Temlyakov, Weak greedy algorithms, Advances in Computational Mathematics, vol.12, issue.2/3, pp.213-227, 2000.
DOI : 10.1023/A:1018917218956

F. J. Theis and E. W. Lang, Formalization of the two-step approach to overcomplete BSS, Proc. SIP 2002, pp.207-212, 2002.

F. J. Theis, C. Puntonet, and E. W. Lang, A histogram-based overcomplete ICA algorithm, Proc. 4th Int. Symp. on Independent Component Anal. and Blind Signal Separation (ICA2003), pp.1071-1076, 2003.

F. J. Theis, A. Jung, C. G. Puntonet, and L. E. , Linear Geometric ICA: Fundamentals and Algorithms, Neural Computation, vol.23, issue.1, pp.419-439, 2003.
DOI : 10.1007/BF00205972
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.378.8118

J. Tropp, Greed is Good: Algorithmic Results for Sparse Approximation, IEEE Transactions on Information Theory, vol.50, issue.10, pp.2231-2242, 2004.
DOI : 10.1109/TIT.2004.834793

J. Tropp, Just relax : Convex programming methods for subset selection and sparse approximation, 2004.

J. Tropp, Just relax: convex programming methods for identifying sparse signals in noise, IEEE Transactions on Information Theory, vol.52, issue.3, pp.1030-1051, 2006.
DOI : 10.1109/TIT.2005.864420

J. A. Tropp, Algorithms for simultaneous sparse approximation. Part II: Convex relaxation, special issue on Sparse Approximations in Signal and Image Processing, pp.589-602, 2006.
DOI : 10.1016/j.sigpro.2005.05.031

J. A. Tropp, A. C. Gilbert, and M. J. Strauss, Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit, special issue on Sparse Approximations in Signal and Image Processing, pp.572-588, 2006.
DOI : 10.1016/j.sigpro.2005.05.030

B. A. Turlach, On algorithms for solving least squares problems under an ? 1 pernalty or an ? 1 constraint, Proc. of the American Statistical Association, volume Statistical Computing Section [CDROM], pp.2572-2577, 2004.

M. Van-hulle, Clustering approach to square and non-square blind source separation, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468), pp.315-323, 1999.
DOI : 10.1109/NNSP.1999.788150

L. Vielva, D. Erdogmus, and J. C. Principe, Underdetermined blind source separation using a probabilistic source sparsity model, Proc. Int. Conf. on ICA and BSS (ICA2001), pp.675-679, 2001.

L. Villemoes, Nonlinear approximation with walsh atoms, Proceedings of " Surface Fitting and Multiresolution Methods, pp.329-336, 1996.
DOI : 10.1007/s003659900046

E. Vincent and R. Gribonval, Construction d'estimateurs oracles pour la séparation de sources, Proc. 20ème colloque GRETSI sur le traitement du signal et des images, 2005.

E. Vincent, R. Gribonval, and M. D. Plumbley, Oracle estimators for the benchmarking of source separation algorithms, Signal Processing, vol.87, issue.8, pp.1933-1950, 2007.
DOI : 10.1016/j.sigpro.2007.01.016
URL : https://hal.archives-ouvertes.fr/inria-00545156

E. Vincent, R. Gribonval, and C. Févotte, Performance measurement in blind audio source separation, IEEE Transactions on Audio, Speech and Language Processing, vol.14, issue.4, pp.1462-1469, 2006.
DOI : 10.1109/TSA.2005.858005
URL : https://hal.archives-ouvertes.fr/inria-00544230

R. Xu, D. Wunsch, and I. , Survey of Clustering Algorithms, IEEE Transactions on Neural Networks, vol.16, issue.3, pp.645-678, 2005.
DOI : 10.1109/TNN.2005.845141

O. Yilmaz and S. Rickard, Blind Separation of Speech Mixtures via Time-Frequency Masking, IEEE Transactions on Signal Processing, vol.52, issue.7, pp.1830-1847, 2004.
DOI : 10.1109/TSP.2004.828896

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, 2001.
DOI : 10.1016/S0042-6989(97)00169-7