M. Vetterli and J. Kovacevic, Wavelets and Subband Coding, 1995.

K. Gröchenig, Foundations of Time-Frequency Analysis, ser, Appl. Numer. Harmon. Anal. Birkhäuser Boston, 2001.

M. Dolson, The Phase Vocoder: A Tutorial, Computer Music Journal, vol.10, issue.4, pp.11-27, 1986.
DOI : 10.2307/3680093

I. Daubechies, A. Grossmann, and Y. Meyer, Painless nonorthogonal expansions, Journal of Mathematical Physics, vol.27, issue.5, pp.1271-1283, 1986.
DOI : 10.1063/1.527388

P. Balazs, M. Dörfler, F. Jaillet, N. Holighaus, and G. A. Velasco, Theory, implementation and applications of nonstationary Gabor frames, Journal of Computational and Applied Mathematics, vol.236, issue.6, pp.1481-1496, 2011.
DOI : 10.1016/j.cam.2011.09.011

N. Holighaus, M. Dörfler, G. Velasco, and T. Grill, A Framework for Invertible, Real-Time Constant-Q Transforms, IEEE Transactions on Audio, Speech, and Language Processing, vol.21, issue.4, pp.775-785, 2013.
DOI : 10.1109/TASL.2012.2234114

J. Brown, spectral transform, The Journal of the Acoustical Society of America, vol.89, issue.1, pp.425-434, 1991.
DOI : 10.1121/1.400476

T. Necciari, P. Balazs, N. Holighaus, and P. Soendergaard, The ERBlet transform: An auditory-based time-frequency representation with perfect reconstruction, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, p.2013
DOI : 10.1109/ICASSP.2013.6637697

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

S. Molla and B. Torrésani, A hybrid scheme for encoding audio signal using hidden Markov models of waveforms, Applied and Computational Harmonic Analysis, vol.18, issue.2, pp.137-166, 2005.
DOI : 10.1016/j.acha.2004.11.001

URL : https://hal.archives-ouvertes.fr/hal-00350467

P. Leveau, E. Vincent, G. Richard, and L. Daudet, Instrument-Specific Harmonic Atoms for Mid-Level Music Representation, IEEE Transactions on Audio, Speech, and Language Processing, vol.16, issue.1, pp.116-128, 2008.
DOI : 10.1109/TASL.2007.910786

URL : https://hal.archives-ouvertes.fr/inria-00544175

D. L. Donoho and M. Elad, Optimally sparse representation in general (nonorthogonal) dictionaries via l1 minimization, the Proceedings of the National Academy of Sciences, pp.2197-2202, 2003.

R. R. Coifman and M. V. Wickerhauser, Entropy-based algorithms for best basis selection, IEEE Transactions on Information Theory, vol.38, issue.2, pp.713-718, 1992.
DOI : 10.1109/18.119732

G. Gasso, A. Rakotomamonjy, and S. Canu, Recovering Sparse Signals With a Certain Family of Nonconvex Penalties and DC Programming, IEEE Transactions on Signal Processing, vol.57, issue.12, pp.4686-4698, 2009.
DOI : 10.1109/TSP.2009.2026004

URL : https://hal.archives-ouvertes.fr/hal-00439453

M. Kowalski and B. Torrésani, Sparsity and persistence: mixed norms provide simple signal models with dependent coefficients, Signal, Image Video Process, pp.251-264, 2008.
DOI : 10.1007/s11760-008-0076-1

URL : https://hal.archives-ouvertes.fr/hal-00206245

M. Yuan and Y. Lin, Model selection and estimation in regression with grouped variables, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.58, issue.1, pp.49-67, 2006.
DOI : 10.1198/016214502753479356

R. Jenatton, J. Audibert, and F. Bach, Structured variable selection with sparsity-inducing norms, J. Mach. Learn. Res, vol.12, pp.2777-2824, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00377732

I. Bayram, Mixed norms with overlapping groups as signal priors, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011.
DOI : 10.1109/ICASSP.2011.5947238

L. Jacob, G. Obozinski, and J. Vert, Group lasso with overlap and graph lasso, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, 2009.
DOI : 10.1145/1553374.1553431

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.7108

M. Zibulevsky and M. Elad, L1-L2 Optimization in Signal and Image Processing, IEEE Signal Processing Magazine, vol.27, issue.3, pp.76-88, 2010.
DOI : 10.1109/MSP.2010.936023

URL : https://hal.archives-ouvertes.fr/inria-00567455

A. Beck and M. 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

M. Kowalski, K. Siedenburg, and M. Dörfler, Social Sparsity! Neighborhood Systems Enrich Structured Shrinkage Operators, IEEE Transactions on Signal Processing, vol.61, issue.10, pp.2498-2511, 2013.
DOI : 10.1109/TSP.2013.2250967

URL : https://hal.archives-ouvertes.fr/hal-00691774

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

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

A. Gramfort, D. Strohmeier, J. Haueisen, M. Hamalainen, and M. Kowalski, Functional Brain Imaging with M/EEG Using Structured Sparsity in Time-Frequency Dictionaries, Neuroimage, vol.70, pp.410-422, 2013.
DOI : 10.1007/978-3-642-22092-0_49

URL : https://hal.archives-ouvertes.fr/inria-00605502

T. S. Lee, Image representation using 2D Gabor wavelets, IEEE Trans. Pattern Anal. Mach. Intell, vol.18, issue.10, pp.959-971, 1996.

P. Soendergaard, B. Torrésani, and P. Balazs, THE LINEAR TIME FREQUENCY ANALYSIS TOOLBOX, International Journal of Wavelets, Multiresolution and Information Processing, vol.10, issue.04, p.1250032, 2012.
DOI : 10.1142/S0219691312500324

URL : https://hal.archives-ouvertes.fr/hal-01221554

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, pp.23-41, 2008.
DOI : 10.1007/s10444-005-9009-5

URL : https://hal.archives-ouvertes.fr/inria-00544767

C. Févotte and S. Godsill, 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

P. Balazs, B. Laback, G. Eckel, and W. A. Deutsch, Time–Frequency Sparsity by Removing Perceptually Irrelevant Components Using a Simple Model of Simultaneous Masking, IEEE Transactions on Audio, Speech, and Language Processing, vol.18, issue.1, pp.34-49, 2010.
DOI : 10.1109/TASL.2009.2023164