A wideband doubly-sparse approach for MIMO sparse filter estimation, Accepted for publication in ICASSP 2011 ,
Sparse filter models for solving permutation indeterminacy in convolutive blind source separation, SPARS'09 ,
URL : https://hal.archives-ouvertes.fr/inria-00369554
A Sparsity-Based Method to Solve Permutation Indeterminacy in Frequency-Domain Convolutive Blind Source Separation, Proc. of Independent Component Analysis and Signal Separation, 2009. ,
DOI : 10.1002/cpa.20131
URL : https://hal.archives-ouvertes.fr/inria-00544760
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, 1920. ,
DOI : 10.1109/TASL.2010.2050089
URL : https://hal.archives-ouvertes.fr/hal-00435897
Sparse Representations in Audio and Music: From Coding to Source Separation, Proceedings of the IEEE, vol.98, issue.6, pp.995-1005, 2010. ,
DOI : 10.1109/JPROC.2009.2030345
URL : https://hal.archives-ouvertes.fr/inria-00489524
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
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
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
A Robust Method to Count and Locate Audio Sources in a Multichannel Underdetermined Mixture, IEEE Transactions on Signal Processing, vol.58, issue.1, pp.121-133, 2010. ,
DOI : 10.1109/TSP.2009.2030854
URL : https://hal.archives-ouvertes.fr/inria-00489529
A deterministic approach to blind identification of multi-channel FIR systems, Proc. of ICASSP, pp.581-584, 1994. ,
Sparse equalization for real-time digital underwater acoustic communications, 'Challenges of Our Changing Global Environment'. Conference Proceedings. OCEANS '95 MTS/IEEE, pp.1417-1422, 1920. ,
DOI : 10.1109/OCEANS.1995.528671
Deconvolution of marine seismic data using the l1 norm, Geophysical Journal International, vol.72, issue.1, pp.93-100, 1920. ,
DOI : 10.1111/j.1365-246X.1983.tb02806.x
Tap-selectable decision-feedback equalization, IEEE Transactions on Communications, vol.45, issue.12, pp.1497-1500, 1920. ,
DOI : 10.1109/26.650219
Blind signal separation: statistical principles, Proceedings of the IEEE, vol.86, issue.10, pp.2009-2026, 1998. ,
DOI : 10.1109/5.720250
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.7237
Elements of information theory, p.31, 1991. ,
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
Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture, Signal Processing, vol.24, issue.1, pp.1-10, 1991. ,
DOI : 10.1016/0165-1684(91)90079-X
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
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
Blind Identification Of Independent Components With Higher-order Statistics, Workshop on Higher-Order Spectral Analysis, pp.157-160, 1989. ,
DOI : 10.1109/HOSA.1989.735288
High-Order Contrasts for Independent Component Analysis, Neural Computation, vol.140, issue.1, pp.157-192, 1999. ,
DOI : 10.1109/78.599941
Blind separation of instantaneous mixture of sources via the gaussian mutual information criterion, Signal Processing, vol.81, issue.4, pp.855-870, 2001. ,
Jacobi Angles for Simultaneous Diagonalization, SIAM Journal on Matrix Analysis and Applications, vol.17, issue.1, pp.161-164, 1996. ,
DOI : 10.1137/S0895479893259546
A survey of convolutive blind source separation methods, p.33, 2007. ,
Blind separation of convolved sources based on information maximization, Neural Networks for Signal Processing VI. Proceedings of the 1996 IEEE Signal Processing Society Workshop, pp.423-432, 1996. ,
DOI : 10.1109/NNSP.1996.548372
Blind separation of delayed and convolved sources Advances in neural information processing systems, pp.758-764, 1997. ,
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way, p.110, 2008. ,
Grouping Separated Frequency Components by Estimating Propagation Model Parameters in Frequency-Domain Blind Source Separation, Audio, Speech, and Language Processing, pp.1592-1604, 2007. ,
DOI : 10.1109/TASL.2007.899218
Blind separation of convolutive audio mixtures using nonstationarity, Proceedings of ICA, pp.975-980, 2003. ,
Convolutive blind separation of non-stationary sources, IEEE Transactions on Speech and Audio Processing, vol.8, issue.3, pp.320-327, 2000. ,
DOI : 10.1109/89.841214
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
A new learning algorithm for blind signal separation, Advances in Neural Information Processing Systems, pp.757-763, 1996. ,
Blind source separation of more sources than mixtures using overcomplete representations, IEEE Signal Processing Letters, vol.6, pp.87-90, 1999. ,
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
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
Sparse Approximate Solutions to Linear Systems, SIAM Journal on Computing, vol.24, issue.2, pp.227-234, 1995. ,
DOI : 10.1137/S0097539792240406
From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images, SIAM Review, vol.51, issue.1, pp.34-81, 2009. ,
DOI : 10.1137/060657704
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
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
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
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
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
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
Dictionary learning and sparse coding for unsupervised clustering, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.2042-2045, 2010. ,
DOI : 10.1109/ICASSP.2010.5494985
URL : http://www.dtic.mil/get-tr-doc/pdf?AD=ADA513140
Survey of Clustering Algorithms, IEEE Transactions on Neural Networks, vol.16, issue.3, pp.645-678, 2005. ,
DOI : 10.1109/TNN.2005.845141
Survey of sparse and non-sparse methods in source separation, IJIST, vol.15, issue.1, pp.18-33, 2005. ,
Blind separation of dependent sources using the "timefrequency ratio of mixtures" approach, Proceedings of the Seventh International Symposium on Signal Processing and Its Applications, pp.81-84, 2003. ,
Temporal and time-frequency correlation-based blind source separation methods. Part I: Determined and underdetermined linear instantaneous mixtures, Signal Processing, vol.87, issue.3, pp.374-407, 2007. ,
DOI : 10.1016/j.sigpro.2006.05.012
URL : https://hal.archives-ouvertes.fr/hal-00270884
A robust method to count and locate audio sources in a stereophonic linear instantaneous mixture, " Independent Component Analysis and Blind Signal Separation, pp.536-543, 2006. ,
Underdetermined Convolutive Blind Source Separation via Time–Frequency Masking, Audio, Speech, and Language Processing, pp.101-116, 2010. ,
DOI : 10.1109/TASL.2009.2024380
A Two-Stage Frequency-Domain Blind Source Separation Method for Underdetermined Convolutive Mixtures, 2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp.139-142, 2007. ,
DOI : 10.1109/ASPAA.2007.4393012
Underdetermined Convolutive Blind Source Separation via Frequency Bin-Wise Clustering and Permutation Alignment, Audio, Speech, and Language Processing, pp.1-1, 2010. ,
DOI : 10.1109/TASL.2010.2051355
Model-Based Expectation-Maximization Source Separation and Localization, Audio, Speech, and Language Processing, pp.382-394, 2010. ,
DOI : 10.1109/TASL.2009.2029711
Just relax: convex programming methods for identifying sparse signals in noise Information Theory, IEEE Transactions on, vol.52, pp.1030-1051, 2006. ,
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
Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition, Proceedings of 27th Asilomar Conference on Signals, Systems and Computers, pp.40-44, 1993. ,
DOI : 10.1109/ACSSC.1993.342465
Sparse Solution of Underdetermined Systems of Linear Equations by Stagewise Orthogonal Matching Pursuit, IEEE Transactions on Information Theory, vol.58, issue.2, p.50, 2006. ,
DOI : 10.1109/TIT.2011.2173241
Uniform Uncertainty Principle and Signal Recovery via??Regularized Orthogonal Matching Pursuit, Foundations of Computational Mathematics, vol.53, issue.12, pp.317-334, 2009. ,
DOI : 10.1007/s10208-008-9031-3
URL : http://arxiv.org/abs/0707.4203
Signal Recovery From Incomplete and Inaccurate Measurements Via Regularized Orthogonal Matching Pursuit, Selected Topics in Signal Processing, pp.310-316, 2010. ,
DOI : 10.1109/JSTSP.2010.2042412
URL : http://arxiv.org/abs/0712.1360
Mptk: Matching Pursuit Made Tractable, 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, pp.496-499, 1950. ,
DOI : 10.1109/ICASSP.2006.1660699
URL : https://hal.archives-ouvertes.fr/inria-00544919
Atomic Decomposition by Basis Pursuit, SIAM Journal on Scientific Computing, vol.20, issue.1, pp.33-61, 1998. ,
DOI : 10.1137/S1064827596304010
Convex Optimization, 1951. ,
CVX: Matlab software for disciplined convex programming (web page and software), p.94, 2009. ,
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
Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society. Series B (Methodological), vol.58, issue.1, pp.267-288, 1996. ,
Least angle regression, The Annals of Statistics, vol.32, issue.2, pp.407-451, 2004. ,
Iteratively reweighted least squares minimization for sparse recovery, Communications on Pure and Applied Mathematics, vol.58, issue.1, pp.1-38, 2010. ,
DOI : 10.1002/cpa.20303
A wide-angle view at iterated shrinkage algorithms, Wavelets XII, pp.26-29, 2007. ,
DOI : 10.1117/12.741299
SMALLbox - An Evaluation Framework for Sparse Representations and Dictionary Learning Algorithms, Latent Variable Analysis and Signal Separation, pp.418-425, 2010. ,
DOI : 10.1007/978-3-642-15995-4_52
URL : https://hal.archives-ouvertes.fr/inria-00574155
Decoding by Linear Programming, IEEE Transactions on Information Theory, vol.51, issue.12, pp.4203-4215, 2005. ,
DOI : 10.1109/TIT.2005.858979
Greed is good: algorithmic results for sparse approximation Information Theory, IEEE Transactions on, vol.50, pp.2231-2242, 2004. ,
On the exponential convergence of matching pursuits in quasi-incoherent dictionaries Information Theory, IEEE Transactions on, vol.52, pp.255-261, 2006. ,
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, pp.655-687, 2008. ,
DOI : 10.1007/s00041-008-9044-y
URL : https://hal.archives-ouvertes.fr/inria-00146660
Sparse and Redundant Representations, p.52, 2010. ,
DOI : 10.1007/978-1-4419-7011-4
URL : https://hal.archives-ouvertes.fr/inria-00568893
Coherence-Based Performance Guarantees for Estimating a Sparse Vector Under Random Noise, IEEE Transactions on Signal Processing, vol.58, issue.10, pp.5030-5043, 2010. ,
DOI : 10.1109/TSP.2010.2052460
URL : https://hal.archives-ouvertes.fr/inria-00567465
ON MINIMUM ENTROPY DECONVOLUTION, p.57, 1981. ,
DOI : 10.1016/B978-0-12-256420-8.50024-1
Identification and deconvolution of multichannel linear non-Gaussian processes using higher order statistics and inverse filter criteria, IEEE Transactions on Signal Processing, vol.45, issue.3, pp.658-672, 1957. ,
DOI : 10.1109/78.558482
Cumulant-based blind identification of linear multi-input-multioutput systems driven by colored inputs, IEEE Transactions on Signal Processing, vol.45, pp.1543-1552, 1957. ,
A Method of Self-Recovering Equalization for Multilevel Amplitude-Modulation Systems, IEEE Transactions on Communications, vol.23, issue.6, pp.679-682, 1957. ,
DOI : 10.1109/TCOM.1975.1092854
A least-squares approach to blind channel identification, IEEE Transactions on Signal Processing, vol.43, issue.57, pp.2982-2993, 1995. ,
Subspace methods for the blind identification of multichannel FIR filters, IEEE Transactions on Signal Processing, vol.43, issue.2, pp.516-525, 1995. ,
DOI : 10.1109/78.348133
A least squares component normalization approach to blind channel identification, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), pp.1797-1800, 1999. ,
DOI : 10.1109/ICASSP.1999.758269
Adaptive multi-channel least mean square and Newton algorithms for blind channel identification, Signal Processing, vol.82, issue.8, pp.1127-1138, 2002. ,
DOI : 10.1016/S0165-1684(02)00247-5
A class of frequency-domain adaptive approaches to blind multichannel identification, Proceedings of the ISSPA, pp.11-24, 2003. ,
DOI : 10.1109/TSP.2002.806559
Blind SIMO channel identification using a sparsity criterion, 2008 IEEE 9th Workshop on Signal Processing Advances in Wireless Communications, pp.271-275, 2008. ,
DOI : 10.1109/SPAWC.2008.4641612
Blind Separation of Underdetermined Convolutive Mixtures Using Their Time–Frequency Representation, Audio, Speech, and Language Processing, pp.1540-1550, 2007. ,
DOI : 10.1109/TASL.2007.898455
Real time separation of convolutive mixtures, Proc. of ICA, pp.65-69, 2001. ,
Blind separation of convolved mixtures in the frequency domain, Neurocomputing, vol.22, issue.1-3, pp.21-34, 1998. ,
DOI : 10.1016/S0925-2312(98)00047-2
Combined approach of array processing and independent component analysis for blind separation of acoustic signals, IEEE Transactions on Speech and Audio Processing, vol.11, issue.3, pp.204-215, 2003. ,
DOI : 10.1109/TSA.2003.809191
A beamforming approach to permutation alignment for multichannel frequency-domain blind source separation, Proc. of ICASSP, pp.881-884, 2002. ,
Evaluation of blind signal separation method using directivity pattern under reverberant conditions, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), pp.3140-3143, 2000. ,
DOI : 10.1109/ICASSP.2000.861203
Permutation Alignment for Frequency Domain ICA Using Subspace Beamforming Methods, Lecture Notes in Computer Science, vol.3195, issue.72, pp.669-676, 2004. ,
DOI : 10.1007/978-3-540-30110-3_85
Geometric source separation: merging convolutive source separation with geometric beamforming, IEEE Transactions on Speech and Audio Processing, vol.10, issue.6, pp.352-362, 2002. ,
DOI : 10.1109/TSA.2002.803443
Video Assisted Speech Source Separation, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., pp.425-428, 2005. ,
DOI : 10.1109/ICASSP.2005.1416331
Maximum likelihood permutation correction for convolutive source separation, Proc. of ICA'03, p.73, 2003. ,
Permutation correction and speech extraction based on split spectrum through fastica, Proc. of ICA'03, p.73, 2003. ,
A survey of convolutive blind source separation, p.72, 2006. ,
A wideband blind identification approach to speech acquisition using a microphone array, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.293-296, 1992. ,
DOI : 10.1109/ICASSP.1992.225914
Beamforming-based convolutive source separation, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., pp.357-60, 2003. ,
DOI : 10.1109/ICASSP.2003.1199958
Blind two-input-two-output FIR channel identification based on frequency domain second-order statistics, IEEE Transactions on Signal Processing, vol.48, issue.2, pp.534-542, 2000. ,
DOI : 10.1109/78.823978
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
The generalized correlation method for estimation of time delay, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.24, issue.4, pp.320-327, 1976. ,
DOI : 10.1109/TASSP.1976.1162830
A new GPCA algorithm for clustering subspaces by fitting, differentiating and dividing polynomials, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., pp.510-517, 0130. ,
DOI : 10.1109/CVPR.2004.1315075
Generalized principal component analysis (GPCA), " Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.27, pp.1945-1959, 2005. ,
DOI : 10.1109/tpami.2005.244
URL : http://arxiv.org/abs/1202.4002