P. Borgnat and P. Flandrin, Time-frequency localization from sparsity constraints, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.3785-3788, 2008.
DOI : 10.1109/ICASSP.2008.4518477

URL : https://hal.archives-ouvertes.fr/ensl-00176412

P. Flandrin and P. Borgnat, Sparse time-frequency distributions of chirps from a compressed sensing perspective, Proc. 8th IMA Int. Conf. on Math. in Signal Proc, pp.84-87, 2008.
URL : https://hal.archives-ouvertes.fr/ensl-00358777

P. Flandrin, Time-frequency and chirps, Proc. SPIE Meeting Wavelet Applications VIII, Conf. No. 8, pp.161-175, 2001.

R. G. Baraniuk, E. Candès, R. Nowak, and M. Vetterli, Compressive Sampling [From the Guest Editors], IEEE Signal Processing Magazine, vol.25, issue.2, pp.12-101, 2008.
DOI : 10.1109/MSP.2008.915557

A. M. Bruckstein, D. L. Donoho, and M. Elad, 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

G. E. Pfander and H. Rauhut, Sparsity in Time-Frequency Representations, Journal of Fourier Analysis and Applications, vol.53, issue.12, 2007.
DOI : 10.1007/s00041-009-9086-9

D. L. Donoho, Compressed sensing, IEEE Transactions on Information Theory, vol.52, issue.4, pp.1289-1306, 2006.
DOI : 10.1109/TIT.2006.871582

URL : https://hal.archives-ouvertes.fr/inria-00369486

E. Candès, J. Romberg, and T. 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

E. Candès and T. Tao, Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?, IEEE Transactions on Information Theory, vol.52, issue.12, pp.5406-5425, 2006.
DOI : 10.1109/TIT.2006.885507

M. Lustig, D. Donoho, and J. M. Pauly, Sparse MRI: The application of compressed sensing for rapid MR imaging, Magnetic Resonance in Medicine, vol.170, issue.6, pp.1182-1195, 2007.
DOI : 10.1002/mrm.21391

M. Lustig, D. Donoho, J. M. Santos, and J. M. Pauly, Compressed Sensing MRI, IEEE Signal Processing Magazine, vol.25, issue.2, pp.72-82, 2008.
DOI : 10.1109/MSP.2007.914728

L. Applebaum, S. D. Howard, S. Searle, and R. Calderbank, Chirp sensing codes: Deterministic compressed sensing measurements for fast recovery, Applied and Computational Harmonic Analysis, vol.26, issue.2, pp.283-290, 2009.
DOI : 10.1016/j.acha.2008.08.002

P. Flandrin, Time-Frequency/Time-Scale Analysis, 1999.

P. Flandrin and P. Gonçalvès, Geometry of Affine Time???Frequency Distributions, Applied and Computational Harmonic Analysis, vol.3, issue.1, pp.10-39, 1996.
DOI : 10.1006/acha.1996.0002

URL : https://hal.archives-ouvertes.fr/inria-00570660

F. Hlawatsch and P. Flandrin, The interference structure of Wigner distribution and related time-frequency representations, The Wigner Distribution ? Theory and Applications in Signal Processing, pp.59-133, 1997.

P. Flandrin, Cross-terms and localization in time-frequency energy distributions, Time-Frequency Signal Analysis and Processing, pp.94-101, 2003.

P. Flandrin, Some features of time-frequency representations of multicomponent signals, ICASSP '84. IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.41-45, 1984.
DOI : 10.1109/ICASSP.1984.1172741

R. G. Baraniuk and D. L. Jones, Signal-dependent time-frequency analysis using a radially Gaussian kernel, Signal Processing, vol.32, issue.3, pp.263-284, 1993.
DOI : 10.1016/0165-1684(93)90001-Q

P. Flandrin, F. Auger, and E. Chassande-mottin, Time-Frequency Reassignment ? From Principles to Algorithms, Applications in Time- Frequency Signal Processing (A. Papandreou-Suppappola, pp.179-203, 2003.
URL : https://hal.archives-ouvertes.fr/hal-00414583

E. Candès and J. Romberg, -MAGIC: Recovery of Sparse Signals via Convex Programming " , User's Guide of the ? 1 -MAGIC toolbox for MATLAB, 2005.

R. G. Baraniuk, P. Flandrin, A. J. Janssen, and O. Michel, Measuring time-frequency information content using the Renyi entropies, IEEE Transactions on Information Theory, vol.47, issue.4, pp.1391-1409, 2001.
DOI : 10.1109/18.923723

R. Price and E. M. Hofstetter, Bounds on the volume and height distributions of the ambiguity function, IEEE Transactions on Information Theory, vol.11, issue.2, pp.207-214, 1965.
DOI : 10.1109/TIT.1965.1053746

S. Qian and J. M. Morris, Wigner Distribution decomposition and cross-terms deleted representation, Signal Processing, vol.27, issue.2, pp.125-144, 1992.
DOI : 10.1016/0165-1684(92)90003-F

S. Qian and D. Chen, Decomposition of the Wigner-Ville distribution and time-frequency distribution series, IEEE Transactions on Signal Processing, vol.42, issue.10, pp.2836-2842, 1994.
DOI : 10.1109/78.324750

M. Figueiredo, R. Nowak, and S. Wright, Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems, Topics in Signal Proc.: Special Issue on Convex Optimization Methods for Signal Processing, pp.586-598, 2007.
DOI : 10.1109/JSTSP.2007.910281

D. Donoho, Y. Tsaig, I. Drori, and J. Starck, Sparse solution of underdetermined linear equations by stagewise orthogonal matching pursuit Report preprint available from http, 2006.

J. A. Tropp and A. Gilbert, Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit, IEEE Transactions on Information Theory, vol.53, issue.12, pp.4655-4666, 2007.
DOI : 10.1109/TIT.2007.909108

D. Needell and J. A. Tropp, CoSaMP, Communications of the ACM, vol.53, issue.12, pp.301-321, 2009.
DOI : 10.1145/1859204.1859229

I. Daubechies, M. Defrise, and C. Demol, 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

I. Daubechies, M. Fornasier, and I. Loris, Accelerated Projected Gradient Method for Linear Inverse Problems with Sparsity Constraints, Journal of Fourier Analysis and Applications, vol.22, issue.1, pp.5-6, 2008.
DOI : 10.1007/s00041-008-9039-8

T. Blumensath and M. E. Davies, Iterative Thresholding for Sparse Approximations, Journal of Fourier Analysis and Applications, vol.73, issue.10, pp.629-654, 2008.
DOI : 10.1007/s00041-008-9035-z

A. Jung, G. Taubck, and F. Hlawatsch, Compressive spectral estimation for nonstationary random processes, Proc. IEEE Int. Conf. on Acoust., Speech and Signal Proc. ICASSP-09, pp.3029-3032, 2009.

A. Jung, G. Taubck, and F. Hlawatsch, Compressive nonstationary spectral estimation using parsimonious random sampling of the ambiguity function, 2009 IEEE/SP 15th Workshop on Statistical Signal Processing, pp.642-645, 2009.
DOI : 10.1109/SSP.2009.5278493

Y. Tsaig, Sparse solution of underdetermined linear systems: Algorithms and applications, 2007.

S. 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, 2001.
DOI : 10.1137/S1064827596304010

D. L. Donoho, M. Elad, and V. N. 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

E. 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

R. Tibshirani, Regression shrinkage and selection via the lasso, J. Royal Statist. Soc. B, vol.58, issue.1, pp.267-288, 1996.

P. Borgnat-was-born-in-poissy and F. , He made his studies at thé Ecole Normale Supérieure de Lyon, France, receiving the Professeur-Agrégé de Sciences Physiques degree in 97, Physics in 99 and defended a Ph.D. degree in Physics and Signal Processing he spent one year in the Signal and Image Processing group of the IRS, 1974.

´. Ens-lyon, His research interests are in statistical signal processing of non-stationary processes (time-frequency representations, time deformations, stationarity tests) and scaling phenomena (time-scale, wavelets) for complex systems (turbulence, networks, He is also working on Internet traffic measurements and modeling, and in analysis and modeling of dynamical complex networks, 2004.

P. Flandrin, He joined CNRS in 1982, where he is currently Research Director Since 1991, he has been with the " Signals, Systems and Physics " Group, within the Physics Department atÉcoleat´atÉcole Normale Supérieure de Lyon, France he spent one semester in Cambridge, UK, as an invited long-term resident of the Isaac Newton Institute for Mathematical Sciences and, from 2002 to 2005, he has been Director of the CNRS national cooperative structure " GdR ISIS His research interests include mainly nonstationary signal processing (with emphasis on time-frequency and time-scale methods) and the study of self-similar stochastic processes. He published many research papers in those areas and he is the author of the book Temps-Fréquence (Paris: Hermès, 1993 and 1998), translated into English as Time-Frequency/Time-Scale Analysis He has been a guest co-editor of the Special Issue " Wavelets and Signal Processing, the IEEE TRANSACTIONS ON SIGNAL PROCESSING in 1993, the Technical Program Chairman of the 1994 IEEE-SP Int. Symp. on Time-Frequency and Time-Scale Analysis and, since 2001, he is the Program Chairman of the French GRETSI Symposium on Signal and Image Processing. He is currently an Associate Editor for the IEEE TRANSACTIONS ON SIGNAL PROCESSING, and he has been a member of the " Signal Processing Theory and Methods " Technical Committee of the IEEE Signal Processing Society, 1978.

. Dr, Flandrin was awarded the Philip Morris Scientific Prize in Mathematics in 1991, the SPIE Wavelet Pioneer Award in 2001 and the Prix Michel Monpetit from the French Academy of Sciences, He is Fellow of IEEE EURASIP, 2001.