. [. Bibliographie, A. Allen, and . Berkeley, Image method for efficiently simulating smallroom acoustics, Journal of the ASA, vol.65, issue.4, pp.943-950, 1979.

J. [. Attouch and . Bolte, On the convergence of the proximal algorithm for nonsmooth functions involving analytic features, Mathematical Programming, vol.4, issue.1-2, pp.5-16, 2009.
DOI : 10.1007/s10107-007-0133-5

URL : https://hal.archives-ouvertes.fr/hal-00803898

. S. Abh-+-10-]-j, N. Abel, P. Bryan, M. Huang, B. Kolar et al., On estimating room impulse responses from recorded balloon pops, Proc. 129th Convention of the AES, 2010.

K. [. Aissa-el-bey, Y. Abed-meraim, and . Grenier, Blind Separation of Underdetermined Convolutive Mixtures Using Their Time–Frequency Representation, IEEE Transactions on Audio, Speech, and Language Processing, vol.15, issue.5, pp.1540-1550, 2007.
DOI : 10.1109/TASL.2007.898455

Y. [. Affes and . Grenier, A signal subspace tracking algorithm for microphone array processing of speech. Speech and Audio Processing, IEEE Transactions on, vol.5, issue.5, pp.425-437, 1997.

J. [. Avendano and . Jot, Frequency domain techniques for stereo to multichannel upmix, Proc. 22nd AES International Conference on Virtual, Synthetic , and Entertainment Audio, number 000251, 2002.

R. S. Araki, S. Mukai, T. Makino, H. Nishikawa, and . Saruwatari, The fundamental limitation of frequency domain blind source separation for convolutive mixtures of speech, IEEE Transactions on Speech and Audio Processing, vol.11, issue.2, pp.109-116, 2003.
DOI : 10.1109/TSA.2003.809193

F. S. Araki, E. Nesta, Z. Vincent, G. Koldovsky, A. Nolte et al., The 2011 Signal Separation Evaluation Campaign (SiSEC2011): - Audio Source Separation -, Proc. 10th International Conference on Latent Variable Analysis and Signal Separation, pp.414-422, 2012.
DOI : 10.1109/JSTSP.2011.2158801

URL : https://hal.archives-ouvertes.fr/hal-00655394

L. [. Ajdler, M. Sbaiz, and . Vetterli, Dynamic measurement of room impulse responses using a moving microphone, The Journal of the Acoustical Society of America, vol.122, issue.3, pp.1636-1645, 2007.
DOI : 10.1121/1.2766776

M. [. Attouch and . Teboulle, Regularized Lotka-Volterra Dynamical System as Continuous Proximal-Like Method in Optimization, Journal of Optimization Theory and Applications, vol.27, issue.3, pp.541-570, 2004.
DOI : 10.1023/B:JOTA.0000037603.51578.45

P. S. Arberet, R. Vandergheynst, J. Carrillo, Y. Thiran, and . Wiaux, Sparse Reverberant Audio Source Separation via Reweighted Analysis, IEEE Transactions on Audio, Speech, and Language Processing, vol.21, issue.7, pp.1391-1402, 2013.
DOI : 10.1109/TASL.2013.2250962

F. [. Benaroya, R. Bimbot, and . 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

P. [. Bolte, J. Combettes, and . Pesquet, Alternating proximal algorithm for blind image recovery, 2010 IEEE International Conference on Image Processing, pp.1673-1676, 2010.
DOI : 10.1109/ICIP.2010.5652173

URL : https://hal.archives-ouvertes.fr/hal-00844115

]. A. Bdvv93, D. Berkhout, P. De-vries, and . Vogel, Acoustic control by wave field synthesis, Journal of the ASA, vol.93, issue.5, pp.2764-2778, 1993.

]. G. Bir46 and . Birkhoff, Three observations on linear algebra, Revista -Universidad Nacional de Tucumán. Serie A, vol.5, pp.147-151, 1946.

B. [. Baumann, D. Kohler, R. Kolossa, and . Orglmeister, Real time separation of convolutive mixtures, Proc. International Congress on Acoustics, pp.65-69, 2001.

R. [. Babacan, M. N. Molina, A. K. Do, and . Katsaggelos, Bayesian Blind Deconvolution with General Sparse Image Priors, Proc. 12th European Conference on Computer Vision, pp.341-355, 2012.
DOI : 10.1007/978-3-642-33783-3_25

]. S. Boy86 and . Boyd, Multitone signals with low crest factor, IEEE Transactions on Circuits and Systems, vol.33, issue.10, pp.1018-1022, 1986.

]. Bra86 and . Bradley, Auditorium acoustics measures from pistol shots, Journal of the ASA, vol.80, issue.1, pp.199-203, 1986.

]. Bra90 and . Bradley, The evolution of newer auditorium acoustics measures, Canadian Acoustics, vol.18, issue.4, pp.13-23, 1990.

P. [. Benichoux, F. Sudhakar, R. Bimbot, and . Gribonval, Well-posedness of the permutation problem in sparse filter estimation with ? p minimi- zation, Applied and Computational Harmonic Analysis, 2011.

P. [. Benichoux, R. Sudhakar, and . Gribonval, Well-posedness of the frequency permutation problem in sparse filter estimation with ? p minimization, Signal Processing with Adaptive Sparse Structured Representations, 2011.

T. [. Brix, J. Sporer, and . Plogsties, CARROUSO-An european approach to 3D-audio, Proc. 110th Convention of the AES, 2001.

L. [. Benichoux, E. Simon, R. Vincent, and . Gribonval, Convex Regularizations for the Simultaneous Recording of Room Impulse Responses, IEEE Transactions on Signal Processing, vol.62, issue.8, 2012.
DOI : 10.1109/TSP.2014.2303431

URL : https://hal.archives-ouvertes.fr/hal-00749585

M. [. Beck and . Teboulle, A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems, SIAM Journal on Imaging Sciences, vol.2, issue.1, pp.183-202, 2009.
DOI : 10.1137/080716542

]. A. Bvg11a, E. Benichoux, R. Vincent, and . Gribonval, A compressed sensing approach to the simultaneous recording of multiple room impulse responses, Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp.285-288, 2011.

]. A. Bvg11b, E. Benichoux, R. Vincent, and . Gribonval, Optimisation convexe pour l'estimation simultanée de réponses acoustiques, Proc. Groupe de Recherche en Traitement du Signal et Images, 2011.

E. [. Benichoux, R. Vincent, and . Gribonval, A fundamental pitfall in blind deconvolution with sparse and shift-invariant priors, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013.
DOI : 10.1109/ICASSP.2013.6638838

URL : https://hal.archives-ouvertes.fr/hal-00800770

C. [. Babaie-zadeh, A. Jutten, and . Mansour, Sparse ICA via cluster-wise PCA, Neurocomputing, vol.69, issue.13-15, pp.1458-1466, 2006.
DOI : 10.1016/j.neucom.2005.12.022

URL : https://hal.archives-ouvertes.fr/hal-00097157

[. 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

]. E. Che53, . T. Cherrychu90-]-w, and . Chu, Some experiments on the recognition of speech, with one and with two ears. The Journal of the acoustical society of America Impulse-response and reverberation-decay measurements made by using a periodic pseudorandom sequence, Applied Acoustics, vol.25, issue.3, pp.975-29193, 1953.

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

S. [. Cho and . Lee, Fast motion deblurring, ACM Transactions on Graphics, vol.28, issue.5 145, 2009.
DOI : 10.1145/1618452.1618491

]. E. Cor06 and . Corteel, Equalization in an extended area using multichannel inversion and wave field synthesis, Journal of the AES, vol.54, issue.12, pp.1140-1161, 2006.

J. [. Candès, T. Romberg, and . Tao, Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information, IEEE Transactions on Information Theory, vol.52, issue.2, pp.489-509, 2006.
DOI : 10.1109/TIT.2005.862083

C. [. Chan and . Wong, Convergence of the alternating minimization algorithm for blind deconvolution, Linear Algebra and its Applications, vol.316, issue.1-3, pp.259-285, 2000.
DOI : 10.1016/S0024-3795(00)00141-5

V. [. Combettes and . Wajs, Signal Recovery by Proximal Forward-Backward Splitting, Multiscale Modeling & Simulation, vol.4, issue.4, pp.1168-1200, 2006.
DOI : 10.1137/050626090

URL : https://hal.archives-ouvertes.fr/hal-00017649

]. G. Dar53 and . Darmois, Analyse générale des liaisons stochastiques : étude particulière de l'analyse factorielle linéaire. Revue de l'Institut international de statistique, pp.2-8, 1953.

[. Dokmanic, M. Yue, M. Lu, and . Vetterli, Can one hear the shape of a room: The 2-D polygonal case, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.321-324, 2011.
DOI : 10.1109/ICASSP.2011.5946405

]. D. Don81 and . Donoho, On minimum entropy deconvolution Applied Time Series AnalysisII, pp.565-609, 1981.

]. D. Don01 and . Donoho, Sparse components of images and optimal atomic decompositions, Constructive Approximation, vol.17, issue.3, pp.353-382, 2001.

]. D. Don06 and . Donoho, For most large underdetermined systems of linear equations the minimal ? 1 -norm solution is also the sparsest solution, Communications on pure and applied mathematics, vol.59, issue.6, pp.797-829, 2006.

P. [. Donoho and . Stark, Uncertainty Principles and Signal Recovery, SIAM Journal on Applied Mathematics, vol.49, issue.3, pp.906-931, 1989.
DOI : 10.1137/0149053

E. [. Duong, R. Vincent, and . Gribonval, An acoustically-motivated spatial prior for under-determined reverberant source separation, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.9-12, 2011.
DOI : 10.1109/ICASSP.2011.5946315

URL : https://hal.archives-ouvertes.fr/inria-00566868

A. [. Elad and . Bruckstein, A generalized uncertainty principle and sparse representation in pairs of bases. Information Theory, IEEE Transactions on, vol.48, issue.9, pp.2558-2567, 2002.

E. [. Elko, T. Diethorn, and . Gänsler, Room impulse response variation due to temperature fluctuations and its impact on acoustic echo cancellation, Proc. International Workshop on Acoustic Echo and Noise Control, pp.67-70, 2003.

R. [. Erkelens and . Heusdens, A statistical room impulse response model with frequency dependent reverberation time for single-microphone late reverberation suppression, Proc. Interspeech, pp.201-204, 2011.

M. [. Eneman and . Moonen, Multimicrophone Speech Dereverberation: Experimental Validation, EURASIP Journal on Audio, Speech, and Music Processing, vol.2007, issue.1, 2007.
DOI : 10.1016/S0167-6393(99)00030-8

]. A. Far00 and . Farina, Simultaneous measurement of impulse response and distortion with a swept-sine technique, Proc. 108th Convention of the AES, pp.18-22, 2000.

N. [. Févotte, J. Bertin, and . Durrieu, Nonnegative Matrix Factorization with the Itakura-Saito Divergence: With Application to Music Analysis, Neural Computation, vol.14, issue.3, pp.793-830, 2009.
DOI : 10.1016/j.sigpro.2007.01.024

. Fsh-+-06-]-r, B. Fergus, A. Singh, S. T. Hertzmann, W. T. Roweis et al., Removing camera shake from a single photograph, ACM Transactions on Graphics, vol.25, issue.3, pp.787-794, 2006.

L. [. Gillespie and . Atlas, Acoustic diversity for improved speech recognition in reverberant environments, IEEE International Conference on Acoustics Speech and Signal Processing, pp.557-560, 2002.
DOI : 10.1109/ICASSP.2002.5743778

[. Grant and S. Boyd, CVX : Matlab software for disciplined convex programming, version 2.0 beta, 2012.

S. [. Gribonval, . [. Lesage, M. Gannot, H. S. Moonen-gillespie, D. Malvar et al., A survey of sparse component analysis for blind source separation : principles, perspectives, and new challenges Subspace methods for multimicrophone speech dereverberation Speech dereverberation via maximum-kurtosis subband adaptive filtering, Proc. 14th European Symposium on Artificial Neural Networks Proc. International Conference on Acoustics, Speech, and Signal Processing, pp.323-3301074, 2001.

F. [. Gorski, K. Pfeuffer, and . Klamroth, Biconvex sets and optimization with biconvex functions: a survey and extensions, Mathematical Methods of Operations Research, vol.21, issue.1, pp.373-407, 2007.
DOI : 10.1007/s00186-007-0161-1

K. [. Gribonval and . Schnass, Dictionary identification -sparse matrixfactorization via ? 1 -minimisation, IEEE Transactions on Information Theory, vol.56, issue.7, pp.3523-3539, 2010.

F. [. Georgiev, A. Theis, and . Cichocki, Sparse Component Analysis and Blind Source Separation of Underdetermined Mixtures, IEEE Transactions on Neural Networks, vol.16, issue.4, pp.992-996, 2005.
DOI : 10.1109/TNN.2005.849840

]. A. Gzpdd04, P. Gonzalez, G. Zuccarello, M. Pinero, and . De-diego, Simultaneous measurement of multichannel acoustic systems, Journal of the AES, vol.52, issue.12, pp.26-42, 2004.

]. P. Hal35 and . Hall, On representatives of subsets, Journal of the London Mathematical Society, vol.10, issue.1, pp.26-30, 1935.

]. E. Hdvb02, D. Hulsebos, E. De-vries, and . Bourdillat, Improved microphone array configurations for auralization of sound fields by wave-field synthesis, Journal of the AES, vol.50, issue.10, pp.779-790, 2002.

S. [. Habets, I. Gannot, P. Cohen, . T. Sommenhyz08-]-e, W. Hale et al., Joint Dereverberation and Residual Echo Suppression of Speech Signals in Noisy Environments, IEEE Transactions on Audio, Speech, and Language Processing, vol.16, issue.8, pp.1433-14511107, 2008.
DOI : 10.1109/TASL.2008.2002071

D. [. Ikram and . Morgan, Exploring permutation inconsistency in blind separation of speech signals in a reverberant environment, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), pp.1041-1044, 2000.
DOI : 10.1109/ICASSP.2000.859141

D. [. Ikram and . Morgan, A beamforming approach to permutation alignment for multichannel frequency-domain blind speech separation, Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.881-884, 2002.

R. [. Jaillet, M. D. Gribonval, H. Plumbley, and . Zayyani, An L1 criterion for dictionary learning by subspace identification, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.5482-5485, 2010.
DOI : 10.1109/ICASSP.2010.5495206

URL : https://hal.archives-ouvertes.fr/hal-00474328

G. [. Jenatton, F. Obozinski, and . Bach, Structured sparse principal component analysis, Proc. International Conference on Artificial Intelligence and Statistics, pp.2777-2824, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00414158

S. [. Knaak, S. Araki, and . Makino, Geometrically constrained independent component analysis. Audio, Speech, and Language Processing, IEEE Transactions on, vol.15, issue.2, pp.715-726, 2007.

M. [. Kinoshita, T. Delcroix, M. Nakatani, and . Miyoshi, Suppression of Late Reverberation Effect on Speech Signal Using Long-Term Multiple-step Linear Prediction, IEEE Transactions on Audio, Speech, and Language Processing, vol.17, issue.4, pp.534-545, 2009.
DOI : 10.1109/TASL.2008.2009015

]. H. Kea-+-09, S. D. Kayser, J. Ewert, T. Anemüller, V. Rohdenburg et al., Database of multichannel in-ear and behind-the-ear head-related and binaural room impulse responses, EURASIP Journal on Advances in Signal Processing, 2009.

R. [. Knappe and . Goubran, Steady-state performance limitations of full-band acoustic echo cancellers, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing, pp.73-7643, 1994.
DOI : 10.1109/ICASSP.1994.389715

R. [. Krueger and . Haeb-umbach, Model-Based Feature Enhancement for Reverberant Speech Recognition, IEEE Transactions on Audio, Speech, and Language Processing, vol.18, issue.7, pp.1692-1707, 2010.
DOI : 10.1109/TASL.2010.2049684

N. [. Kingsbury and . Morgan, Recognizing reverberant speech with RASTA-PLP, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.1259-1262, 1997.
DOI : 10.1109/ICASSP.1997.596174

A. [. Karande, P. Mehta, and . Tripathi, Online bipartite matching with unknown distributions, Proceedings of the 43rd annual ACM symposium on Theory of computing, STOC '11, pp.587-596, 2011.
DOI : 10.1145/1993636.1993715

T. [. Kameoka, T. Nakatani, and . Yoshioka, Robust speech dereverberation based on non-negativity and sparse nature of speech spectrograms, Proc. 9th IEEE International Conference on Acoustics, Speech and Signal Processing, pp.45-48, 2009.

]. M. Kow09 and . Kowalski, Sparse regression using mixed norms, Applied and Computational Harmonic Analysis, vol.27, issue.3, pp.303-324, 2009.

R. [. Kumar, B. Singh, R. Raj, and . Stern, Gammatone sub-band magnitudedomain dereverberation for ASR, Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, pp.4604-4607, 2011.

T. [. Krishnan, R. Tay, and . Fergus, Blind deconvolution using a normalized sparsity measure, CVPR 2011, pp.233-240, 2011.
DOI : 10.1109/CVPR.2011.5995521

]. H. Kut00 and . Kuttruff, Room Acoustics, 2000.

E. [. Kowalski, R. Vincent, and . Gribonval, Beyond the Narrowband Approximation: Wideband Convex Methods for Under-Determined Reverberant Audio Source Separation, IEEE Transactions on Audio, Speech, and Language Processing, vol.18, issue.7, pp.1818-1829, 2010.
DOI : 10.1109/TASL.2010.2050089

URL : https://hal.archives-ouvertes.fr/hal-00435897

J. [. Lebart, P. N. Boucher, and . Denbigh, A new method based on spectral subtraction for speech dereverberation, Acta Acustica united with Acustica, vol.87, issue.3, pp.359-366, 2001.

]. Y. Lckl07a, J. Lin, Y. Chen, D. D. Kim, and . Lee, Blind channel identification for speech dereverberation using ? 1 -norm sparse learning, Advances in Neural Information Processing Systems, pp.921-928, 2007.

]. Y. Lckl07b, J. Lin, Y. Chen, D. D. Kim, and . Lee, Blind sparse-nonnegative (BSN) channel identification for acoustic time-difference-of-arrival estimation, Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp.106-109, 2007.

T. [. Lindau, S. Hohn, and . Weinzierl, Binaural resynthesis for comparative studies of acoustical environments, Proc. 122nd Convention of the AES, 2007.

[. Lee, M. 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.

H. [. Lindau, S. Maempel, ]. A. Weinzierllwdf09, Y. Levin, F. Weiss et al., Minimum BRIR grid resolution for dynamic binaural synthesis Understanding and evaluating blind deconvolution algorithms, Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp.3498-3498, 2008.

]. S. Mal99 and . Mallat, A Wavelet Tour of Signal Processing, 1999.

]. B. Mar70 and . Martinet, Brève communication. régularisation d'inéquations variationnelles par approximations successives, ESAIM : Mathematical Modelling and Numerical Analysis-Modélisation Mathématique et Analyse Numérique, vol.4, issue.R3, pp.154-158, 1970.

P. [. Majdak, B. Balazs, and . Laback, Multiple exponential sweep method for fast measurement of head-related transfer functions, Journal of the AES, vol.55, issue.78, pp.623-637, 2007.

M. [. Mitianoudis and . Davies, Audio source separation of convolutive mixtures, IEEE Transactions on Speech and Audio Processing, vol.11, issue.5, pp.489-497, 2003.
DOI : 10.1109/TSA.2003.815820

M. [. Mitianoudis and . Davies, Permutation Alignment for Frequency Domain ICA Using Subspace Beamforming Methods, Independent Component Analysis and Blind Signal Separation, pp.669-676, 2004.
DOI : 10.1007/978-3-540-30110-3_85

L. [. Mignot, F. Daudet, and . Ollivier, Compressed sensing for acoustic response reconstruction: Interpolation of the early part, 2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp.225-228, 2011.
DOI : 10.1109/ASPAA.2011.6082298

URL : https://hal.archives-ouvertes.fr/hal-00766979

S. [. Money and . Kang, Total variation minimizing blind deconvolution with shock filter reference, Image and Vision Computing, vol.26, issue.2, pp.302-314, 2008.
DOI : 10.1016/j.imavis.2007.06.005

]. H. Møl92 and . Møller, Fundamentals of binaural technology Applied acoustics, pp.171-218, 1992.

[. Moreau, Fonctions convexes duales et points proximaux dans un espace hilbertien. Comptes Rendus de l'Académie des, Sciences Série A, vol.255, pp.2897-2899, 1962.

]. J. Mou85 and . Mourjopoulos, On the variation and invertibility of room impulse response functions, Journal of Sound and Vibration, vol.102, issue.2, pp.217-228, 1985.

N. [. Macwilliams and . Sloane, Pseudo-random sequences and arrays, Proceedings of the IEEE, pp.1715-1729, 1976.
DOI : 10.1109/PROC.1976.10411

C. [. Møller, M. F. Sørensen, D. Jensen, and . Hammershøi, Binaural technique : Do we need individual recordings, Journal of the AES, vol.44, issue.6, pp.451-469, 1996.

N. [. Naylor, . [. Gaubitch, K. Nakatani, M. Kinoshita, and . Miyoshi, Speech Dereverberation Harmonicity-based blind dereverberation for single-channel speech signals, IEEE Transactions on Audio, Speech, and Language Processing, vol.15, issue.1, pp.80-95, 2007.

L. [. Novak, F. Simon, P. Kadlec, and . Lotton, Nonlinear System Identification Using Exponential Swept-Sine Signal, IEEE Transactions on Instrumentation and Measurement, vol.59, issue.8, pp.2220-2229, 2010.
DOI : 10.1109/TIM.2009.2031836

. Nyk-+-10-]-t, T. Nakatani, K. Yoshioka, M. Kinoshita, B. Miyoshi et al., Speech dereverberation based on variance-normalized delayed linear prediction, IEEE Transactions on Acoustics Speech and Signal Processing, vol.18, issue.7, pp.1717-1731, 2010.

B. [. O-'grady, S. T. Pearlmutter, and . Rickard, Survey of sparse and non-sparse methods in source separation, International Journal of Imaging Systems and Technology, vol.47, issue.33, pp.18-33, 2005.
DOI : 10.1002/ima.20035

E. [. Ozerov, F. Vincent, and . Bimbot, A General Flexible Framework for the Handling of Prior Information in Audio Source Separation, IEEE Transactions on Audio, Speech, and Language Processing, vol.20, issue.4, pp.1118-1133, 2012.
DOI : 10.1109/TASL.2011.2172425

URL : https://hal.archives-ouvertes.fr/inria-00536917

]. J. Oxl92, . Oxleypa02-]-l, C. Parra, and . Alvino, Matroid theory Geometric source separation : Merging convolutive source separation with geometric beamforming, IEEE Transactions on Speech and Audio Processing, vol.21, issue.106, pp.352-362, 1992.

A. [. Princen and . Bradley, Analysis synthesis filter bank design based on time domain aliasing cancellation. Acoustics, Speech and Signal Processing, IEEE Transactions on, vol.34, issue.5, pp.1153-1161, 1986.
DOI : 10.1109/tassp.1986.1164954

S. [. Parikh and . Boyd, Proximal algorithms. Foundations and Trends in Optimization, pp.1-96, 2013.
DOI : 10.1561/2400000003

T. [. Plumbley, L. Blumensath, M. E. Daudet, R. Gribonval, and . Davies, Sparse Representations in Audio and Music: From Coding to Source Separation, Proceedings of the IEEE, pp.995-1005, 2010.
DOI : 10.1109/JPROC.2009.2030345

URL : https://hal.archives-ouvertes.fr/inria-00489524

P. Peretti, S. Cecchi, L. Romoli, and F. Piazza, Performance evaluation of adaptive algorithms for wave field analysis/synthesis using sound field simulations [Pen56] R. Penrose. On best approximate solutions of linear matrix equations, Computational Simulations and Applications, chapter 25 Proceedings of the Cambridge Philosophical Society, pp.17-19, 1956.

E. [. Puigt, Y. Vincent, and . Deville, Validity of the Independence Assumption for the Separation of Instantaneous and Convolutive Mixtures of Speech and Music Sources, Independent Component Analysis and Signal Separation, pp.613-620, 2009.
DOI : 10.1016/j.sigpro.2006.02.032

URL : https://hal.archives-ouvertes.fr/inria-00544163

A. [. Pearlmutter and . Zador, Monaural Source Separation Using Spectral Cues, Proc. International Conference on Independent Component Analysis and Blind Signal Separation, pp.478-485, 2004.
DOI : 10.1007/978-3-540-30110-3_61

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.2253

]. R. Roc97 and . Rockafellar, Convex analysis, 1997.

]. S. Row00 and . Roweis, One microphone source separation, NIPS, pp.793-799, 2000.

J. [. Rahbar and . Reilly, A frequency domain method for blind source separation of convolutive audio mixtures. Speech and Audio Processing, IEEE Transactions on, vol.13, issue.5, pp.832-844, 2005.

R. [. Rabiner and . Schafer, Digital processing of speech signals, IET, vol.19, 1979.

S. [. Sudhakar, R. H. Arberet, S. Sawada, R. Araki, S. Mukai et al., Double sparsity : Towards blind estimation of multiple channels Grouping separated frequency components by estimating propagation model parameters in frequency-domain blind source separation, Proc. International Conference on Latent Variable Analysis and Signal Separation, pp.571-578, 2007.

J. [. Smaragdis and . Brown, Non-negative matrix factorization for polyphonic music transcription, 2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (IEEE Cat. No.03TH8684), pp.177-180, 2003.
DOI : 10.1109/ASPAA.2003.1285860

]. M. Sch65 and . Schroeder, New method of measuring reverberation time, Journal of the ASA, vol.37, issue.3, pp.409-412, 1965.

]. M. Sch79 and . Schroeder, Integrated-impulse method measuring sound decay without using impulses, Journal of the ASA, vol.66, pp.497-500, 1979.

L. [. Shen, L. Du, W. Zhang, and . Gong, A blind restoration method for remote sensing images. Geoscience and Remote Sensing Letters, IEEE, issue.96, pp.1137-1141, 2012.

J. [. Stan, D. Embrechts, and . Archambeau, Comparison of different impulse response measurement techniques, Journal of the AES, vol.50, issue.4, pp.249-262, 2002.

R. [. Sudhakar and . Gribonval, A Sparsity-Based Method to Solve Permutation Indeterminacy in Frequency-Domain Convolutive Blind Source Separation, Independent Component Analysis and Signal Separation, pp.338-345, 2009.
DOI : 10.1002/cpa.20131

URL : https://hal.archives-ouvertes.fr/inria-00544760

J. [. Shan, A. Jia, and . Agarwala, High-quality motion deblurring from a single image, ACM Transactions on Graphics (TOG), vol.27, issue.3 73, 2008.

P. [. Sinkhorn, H. Knopp, R. Sawada, S. Mukai, S. Araki et al., Concerning nonnegative matrices and doubly stochastic matrices A robust and precise method for solving the permutation problem of frequency-domain blind source separation, Pacific Journal of Mathematics IEEE Transactions on Speech and Audio Processing, vol.21, issue.125, pp.343-348530, 1967.

R. [. Sehr, W. Maas, and . Kellermann, Reverberation Model-Based Decoding in the Logmelspec Domain for Robust Distant-Talking Speech Recognition, IEEE Transactions on Audio, Speech, and Language Processing, vol.18, issue.7, pp.1676-1691, 2010.
DOI : 10.1109/TASL.2010.2050511

D. [. Servière and . Pham, A Novel Method for Permutation Correction in Frequency-Domain in Blind Separation of Speech Mixtures, Proc. 5th International Conference on Independent Component Analysis and Blind Signal Separation, pp.807-815, 2004.
DOI : 10.1007/978-3-540-30110-3_102

]. W. Sta73 and . Stahnke, Primitive binary polynomials, Mathematics of Computation, vol.27, issue.124, pp.977-980, 1973.

]. P. Sud11, . Sudhakara, and . Murthy, Sparse Models and Convex Optimisation for Convolutive Blind Source Separation, 2011.

W. [. Sanei, J. A. Wang, and . Chambers, A coupled HMM for solving the permutation problem in frequency domain BSS, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.565-568, 2004.
DOI : 10.1109/ICASSP.2004.1327173

]. T. Tao05 and . Tao, An uncertainty principle for cyclic groups of prime order, Mathematical Research Letters, vol.12, pp.121-127, 2005.

]. J. Tro08 and . Tropp, On the linear independence of spikes and sines, Journal of Fourier Analysis and Applications, vol.14, pp.838-858, 2008.

K. [. Theis, T. Stadlthanner, and . Tanaka, First results on uniqueness of sparse non-negative matrix factorization, Proc.13th European Signal Processing Conference, 2005.

]. H. Van02, Van Trees. Optimum array processing, 2002.

]. E. Vat-+-12, S. Vincent, F. J. Araki, G. Theis, P. Nolte et al., The Signal Separation Evaluation Campaign Achievements and remaining challenges, Signal Processing, vol.92, pp.1928-1936, 2007.

[. Virtanen, A. T. Cemgil, and S. Godsill, Bayesian extensions to non-negative matrix factorisation for audio signal modelling, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.1825-1828, 2008.
DOI : 10.1109/ICASSP.2008.4517987

[. Neumann, 1. A Certain Zero-sum Two-person Game Equivalent to the Optimal Assignment Problem, Contributions to the Theory of Games, pp.5-12, 1953.
DOI : 10.1515/9781400881970-002

URL : https://hal.archives-ouvertes.fr/hal-00843029

J. [. Wang, S. Chambers, and . Sanei, A Novel Hybrid Approach to the Permutation Problem of Frequency Domain Blind Source Separation, Proc. International Conference on Independent Component Analysis and Blind Signal Separation, pp.532-539, 2004.
DOI : 10.1007/978-3-540-30110-3_68

D. [. Wightman and . Kistler, Headphone simulation of free???field listening. I: Stimulus synthesis, The Journal of the Acoustical Society of America, vol.85, issue.2, pp.858-867, 1989.
DOI : 10.1121/1.397557

W. [. Winter, H. Kellermann, S. Sawada, and . Makino, MAP-based underdetermined blind source separation of convolutive mixtures by hierarchical clustering and l1-norm minimization, EURASIP Journal on Applied Signal Processing, issue.1, pp.81-81, 2007.

]. M. Wri95 and . Wright, Comments on aspects of MLS measuring systems, Journal of the AES, vol.43, issue.1, pp.48-49, 1995.

H. [. Xu, L. Liu, T. Tong, and . Kailath, A least-squares approach to blind channel identification, IEEE Transactions on Signal Processing, issue.12, pp.432982-2993, 1995.

T. [. Yoshioka, M. Nakatani, and . Miyoshi, Integrated Speech Enhancement Method Using Noise Suppression and Dereverberation, IEEE Transactions on Audio, Speech, and Language Processing, vol.17, issue.2, pp.231-246, 2009.
DOI : 10.1109/TASL.2008.2008042

S. [. Yilmaz and . 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

T. [. Zheng, W. Falk, and . Chan, An assessment of the improvement potential of time-frequency masking for speech dereverberation, Proc. 12th Interspeech, pp.205-208, 2011.

B. [. Zibulevsky and . 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

D. Vue-logarithmique, une des réponses esitimées par P 1,? pour T =0 .45 T crit , c c m p a r é eàl av é r i t ét e r r a i n, p.63

.. Rôle-du-paramètre-de-l, enveloppe t R sur la précision des réponses estimées pour T =0.45 T crit, p.64