Applied multiway data analysis, 2008. ,
DOI : 10.1002/9780470238004
Tensors : A brief introduction, IEEE Signal Processing Magazine, vol.31, issue.3, pp.44-53, 2014. ,
DOI : 10.1109/MSP.2014.2298533
URL : https://hal.archives-ouvertes.fr/hal-00923279
Low-rank decomposition of multi-way arrays: a signal processing perspective, Processing Workshop Proceedings, 2004 Sensor Array and Multichannel Signal, pp.52-58, 2004. ,
DOI : 10.1109/SAM.2004.1502907
Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysis, IEEE Signal Processing Magazine, vol.32, issue.2, pp.145-163, 2015. ,
DOI : 10.1109/MSP.2013.2297439
A survey of tensor methods, 2009 IEEE International Symposium on Circuits and Systems, pp.2773-2776, 2009. ,
DOI : 10.1109/ISCAS.2009.5118377
Tensor Decompositions and Applications, SIAM Review, vol.51, issue.3, pp.455-500, 2009. ,
DOI : 10.1137/07070111X
Parallel Randomly Compressed Cubes : A scalable distributed architecture for big tensor decomposition, IEEE Signal Processing Magazine, vol.31, issue.5, pp.57-70, 2014. ,
DOI : 10.1109/MSP.2014.2329196
Era of big data processing: A new approach via tensor networks and tensor decompositions, arXiv preprint, 2014. ,
A Tensor-Based Approach for Big Data Representation and Dimensionality Reduction, IEEE Transactions on Emerging Topics in Computing, vol.2, issue.3, pp.280-291, 2014. ,
DOI : 10.1109/TETC.2014.2330516
Fast Multilinear Singular Value Decomposition for Structured Tensors, SIAM Journal on Matrix Analysis and Applications, vol.30, issue.3, pp.1008-1021, 2008. ,
DOI : 10.1137/060655936
Fast multilinear Singular Value Decomposition for higher-order Hankel tensors, 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2014. ,
DOI : 10.1109/SAM.2014.6882436
Structured tensor computations: Blocking, symmetries and kronecker factorizations, 2012. ,
Fast Hankel tensor-vector product and its application to exponential data fitting, Numerical Linear Algebra with Applications, 2015. ,
DOI : 10.1002/nla.1970
Three dimensional strongly symmetric circulant tensors, Linear Algebra and its Applications, vol.482, pp.207-220, 2015. ,
DOI : 10.1016/j.laa.2015.05.024
Fast orthogonal decomposition of Volterra cubic kernels using oblique unfolding, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ,
DOI : 10.1109/ICASSP.2011.5947249
URL : https://hal.archives-ouvertes.fr/hal-00576019
Tensor CP Decomposition with Structured Factor Matrices: Algorithms and Performance Available: https, IEEE Journal of Selected Topics in Signal Processing, 2016. ,
Higher-Order SVD-Based Subspace Estimation to Improve the Parameter Estimation Accuracy in Multidimensional Harmonic Retrieval Problems, IEEE Transactions on Signal Processing, vol.56, issue.7, pp.3198-3213, 2008. ,
DOI : 10.1109/TSP.2008.917929
Tensor Algebra and Multidimensional Harmonic Retrieval in Signal Processing for MIMO Radar, IEEE Transactions on Signal Processing, vol.58, issue.11, pp.5693-5705, 2010. ,
DOI : 10.1109/TSP.2010.2058802
Deterministic asymptotic Cram??r???Rao bound for the multidimensional harmonic model, Signal Processing, vol.88, issue.12, pp.2869-2877, 2008. ,
DOI : 10.1016/j.sigpro.2008.06.011
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
Compressive Sensing [Lecture Notes], IEEE Signal Processing Magazine, vol.24, issue.4, pp.118-121, 2007. ,
DOI : 10.1109/MSP.2007.4286571
Decoding by Linear Programming, IEEE Transactions on Information Theory, vol.51, issue.12, pp.4203-4215, 2005. ,
DOI : 10.1109/TIT.2005.858979
Sampling-50 years after Shannon, Proceedings of the IEEE, vol.88, issue.4, pp.569-587, 2000. ,
DOI : 10.1109/5.843002
An Introduction To Compressive Sampling, IEEE Signal Processing Magazine, vol.25, issue.2, pp.21-30, 2008. ,
DOI : 10.1109/MSP.2007.914731
Shannon-Theoretic Limits on Noisy Compressive Sampling, IEEE Transactions on Information Theory, vol.56, issue.1, pp.492-504, 2010. ,
DOI : 10.1109/TIT.2009.2034796
Direction estimation using compressive sampling array processing, 2009 IEEE/SP 15th Workshop on Statistical Signal Processing, pp.626-629, 2009. ,
DOI : 10.1109/SSP.2009.5278497
Compressive wireless sensing, Proceedings of the 5th International Conference on Information Processing in Sensor Networks, pp.134-142, 2006. ,
Compressive video sampling, 16th European Signal Processing Conference, pp.1-5, 2008. ,
MIMO Radar Using Compressive Sampling, IEEE Journal of Selected Topics in Signal Processing, vol.4, issue.1, pp.146-163, 2010. ,
DOI : 10.1109/JSTSP.2009.2038973
Compressive Sensing of Sparse Tensors, IEEE Transactions on Image Processing, vol.23, issue.10, pp.4438-4447, 2014. ,
DOI : 10.1109/TIP.2014.2348796
Multi-Way Compressed Sensing for Sparse Low-Rank Tensors, IEEE Signal Processing Letters, vol.19, issue.11, pp.757-760, 2012. ,
DOI : 10.1109/LSP.2012.2210872
Multidimensional compressed sensing and their applications, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol.34, issue.7, pp.355-380, 2013. ,
DOI : 10.1002/widm.1108
Multiarray signal processing: Tensor decomposition meets compressed sensing, Comptes Rendus M??canique, vol.338, issue.6, pp.311-320, 2010. ,
DOI : 10.1016/j.crme.2010.06.005
URL : https://hal.archives-ouvertes.fr/hal-00512271
Block-Sparse Signals: Uncertainty Relations and Efficient Recovery, IEEE Transactions on Signal Processing, vol.58, issue.6, pp.3042-3054, 2010. ,
DOI : 10.1109/TSP.2010.2044837
On the Reconstruction of Block-Sparse Signals With an Optimal Number of Measurements, IEEE Transactions on Signal Processing, vol.57, issue.8, pp.3075-3085, 2009. ,
DOI : 10.1109/TSP.2009.2020754
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
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
Compressive MUSIC: Revisiting the Link Between Compressive Sensing and Array Signal Processing, IEEE Transactions on Information Theory, vol.58, issue.1, pp.278-301, 2012. ,
DOI : 10.1109/TIT.2011.2171529
Compressive Sampling of Multiple Sparse Signals Having Common Support Using Finite Rate of Innovation Principles, IEEE Signal Processing Letters, vol.18, issue.5, pp.331-334, 2011. ,
DOI : 10.1109/LSP.2011.2131649
Fundamentals of statistical signal processing: estimation theory, 1993. ,
Spectral analysis of signals, NJ, 2005. ,
On the Achievability of Cram??r???Rao Bound in Noisy Compressed Sensing, IEEE Transactions on Signal Processing, vol.60, issue.1, pp.518-526, 2012. ,
DOI : 10.1109/TSP.2011.2171953
Asymptotic Achievability of the CramÉr–Rao Bound for Noisy Compressive Sampling, IEEE Transactions on Signal Processing, vol.57, issue.3, pp.1233-1236, 2009. ,
DOI : 10.1109/TSP.2008.2010379
The Cramér-Rao Bound for Estimating a Sparse Parameter Vector, IEEE Transactions on Signal Processing, vol.58, issue.6, pp.3384-3389, 2010. ,
DOI : 10.1109/TSP.2010.2045423
Cramér-Rao-Type Bounds for Sparse Bayesian Learning, IEEE Transactions on Signal Processing, vol.61, issue.3, pp.622-632, 2013. ,
DOI : 10.1109/TSP.2012.2226165
Oracle performance estimation of Bernoulli-distributed sparse vectors, 2016 IEEE Statistical Signal Processing Workshop (SSP), 2016. ,
DOI : 10.1109/SSP.2016.7551780
URL : https://hal.archives-ouvertes.fr/hal-01313460
Compressed Sensing with Basis Mismatch: Performance Bounds and Sparse-Based Estimator, IEEE Transactions on Signal Processing, vol.64, issue.13, pp.3483-3494, 2016. ,
DOI : 10.1109/TSP.2016.2544742
URL : https://hal.archives-ouvertes.fr/hal-01313459
Joint Source Estimation and Localization, IEEE Transactions on Signal Processing, vol.63, issue.10, pp.2485-2495, 2015. ,
DOI : 10.1109/TSP.2015.2404311
URL : https://hal.archives-ouvertes.fr/hal-01005352
Cramér-Rao lower bounds for lowrank decomposition of multidimensional arrays, IEEE Transactions on Signal Processing, vol.49, issue.9, pp.2074-2086, 2001. ,
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
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
CoSaMP, Communications of the ACM, vol.53, issue.12, pp.301-321, 2009. ,
DOI : 10.1145/1859204.1859229
Atomic Decomposition by Basis Pursuit, SIAM Journal on Scientific Computing, vol.20, issue.1, pp.33-61, 1998. ,
DOI : 10.1137/S1064827596304010
Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society. Series B, pp.267-288, 1996. ,
Iterative hard thresholding for compressed sensing, Applied and Computational Harmonic Analysis, vol.27, issue.3, pp.265-274, 2009. ,
DOI : 10.1016/j.acha.2009.04.002
Sampling signals with finite rate of innovation, IEEE Transactions on Signal Processing, vol.50, issue.6, pp.1417-1428, 2002. ,
DOI : 10.1109/TSP.2002.1003065
Innovation Rate Sampling of Pulse Streams With Application to Ultrasound Imaging, IEEE Transactions on Signal Processing, vol.59, issue.4, pp.1827-1842, 2011. ,
DOI : 10.1109/TSP.2011.2105480
Sampling Schemes for Multidimensional Signals With Finite Rate of Innovation, IEEE Transactions on Signal Processing, vol.55, issue.7, pp.3670-3686, 2007. ,
DOI : 10.1109/TSP.2007.894259
Subspace Methods for Joint Sparse Recovery, IEEE Transactions on Information Theory, vol.58, issue.6, pp.3613-3641, 2012. ,
DOI : 10.1109/TIT.2012.2189196
A sparse signal reconstruction perspective for source localization with sensor arrays, IEEE Transactions on Signal Processing, vol.53, issue.8, pp.3010-3022, 2005. ,
DOI : 10.1109/TSP.2005.850882
A mathematical introduction to compressive sensing, 2013. ,
DOI : 10.1007/978-0-8176-4948-7
Compressed sensing with coherent and redundant dictionaries, Applied and Computational Harmonic Analysis, vol.31, issue.1, pp.59-73, 2011. ,
DOI : 10.1016/j.acha.2010.10.002
A simple proof that random matrices are democratic, arXiv preprint, 2009. ,
Linear estimation, NJ, vol.1, 2000. ,
Some mathematical notes on three-mode factor analysis, Psychometrika, vol.64, issue.3, pp.279-311, 1966. ,
DOI : 10.1007/BF02289464
Tensor-based algorithms for learning multidimensional separable dictionaries, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.3963-3967, 2014. ,
DOI : 10.1109/ICASSP.2014.6854345
Fast compressive sensing of highdimensional signals with tree-structure sparsity pattern, 2014 IEEE China Summit & International Conference on Signal and Information Processing, pp.738-742, 2014. ,
Double Sparsity: Learning Sparse Dictionaries for Sparse Signal Approximation, IEEE Transactions on Signal Processing, vol.58, issue.3, pp.1553-1564, 2010. ,
DOI : 10.1109/TSP.2009.2036477
Closed-Form MMSE Estimation for Signal Denoising Under Sparse Representation Modeling Over a Unitary Dictionary, IEEE Transactions on Signal Processing, vol.58, issue.7, pp.3471-3484, 2010. ,
DOI : 10.1109/TSP.2010.2046596
URL : https://hal.archives-ouvertes.fr/inria-00577220
Sparsity pattern recovery in Bernoulli- Gaussian signal model, 2010. ,
Bayesian Compressive Sensing Via Belief Propagation, IEEE Transactions on Signal Processing, vol.58, issue.1, pp.269-280, 2010. ,
DOI : 10.1109/TSP.2009.2027773
Nonparametric regression using Bayesian variable selection, Journal of Econometrics, vol.75, issue.2, pp.317-343, 1996. ,
DOI : 10.1016/0304-4076(95)01763-1
Fast bayesian matching pursuit, 2008 Information Theory and Applications Workshop, pp.326-333, 2008. ,
DOI : 10.1109/ITA.2008.4601068
Bayesian Orthogonal Component Analysis for Sparse Representation, IEEE Transactions on Signal Processing, vol.58, issue.5, pp.2675-2685, 2010. ,
DOI : 10.1109/TSP.2010.2041594
URL : https://hal.archives-ouvertes.fr/hal-00548753
A sparse signal reconstruction perspective for source localization with sensor arrays, IEEE Transactions on Signal Processing, vol.53, issue.8, 2003. ,
DOI : 10.1109/TSP.2005.850882
Compressed Beamforming in Ultrasound Imaging, IEEE Transactions on Signal Processing, vol.60, issue.9, pp.4643-4657, 2012. ,
DOI : 10.1109/TSP.2012.2200891
Robust adaptive beamforming, 2006. ,
DOI : 10.1002/0471733482
Fundamentals of statistical signal processing: Detection theory, 1998. ,
Toward a theory of information processing, Signal Processing, vol.87, issue.6, pp.1326-1344, 2007. ,
DOI : 10.1016/j.sigpro.2006.11.005
Elements of information theory, 1991. ,
On a symmetric divergence measure and information inequalities, Journal of Inequalities in pure and applied Mathematics, vol.6, issue.3, 2005. ,
Generalized Orthogonal Matching Pursuit, IEEE Transactions on Signal Processing, vol.60, issue.12, pp.6202-6216, 2012. ,
DOI : 10.1109/TSP.2012.2218810
Matrix computations, 2012. ,
Cramer- Rao Bound for Finite Streams of an Arbitrary Number of Pulses, EUSIPCO'14, p.p. nc, 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-01005005
Sampling FRI signals with the SOS kernel: Bounds and optimal kernel, 2015 23rd European Signal Processing Conference (EUSIPCO), pp.2172-2176, 2015. ,
DOI : 10.1109/EUSIPCO.2015.7362769
URL : https://hal.archives-ouvertes.fr/hal-01159937
Theory of point estimation, 1998. ,
The trimmed mean, " in Asymptotic Theory of Statistics and Probability, ser. Springer Texts in Statistics, pp.271-278, 2008. ,
Communication systems engineering, 1994. ,
Multiple-antenna capacity in the low-power regime, IEEE Transactions on Information Theory, vol.49, issue.10, pp.2527-2544, 2003. ,
DOI : 10.1109/TIT.2003.817429
Random matrix methods for wireless communications, 2011. ,
DOI : 10.1017/CBO9780511994746
URL : https://hal.archives-ouvertes.fr/hal-00658725
Closed Form Summation for Classical Distributions: Variations on a Theme of De Moivre, Statistical Science, vol.6, issue.3, pp.284-302, 1991. ,
DOI : 10.1214/ss/1177011699
A Note on the Negative Moments of a Truncated Poisson Variate, Journal of the American Statistical Association, vol.24, issue.308, pp.1220-1224, 1964. ,
DOI : 10.1214/aoms/1177731170
Interpreting Kullback???Leibler divergence with the Neyman???Pearson lemma, Journal of Multivariate Analysis, vol.97, issue.9, pp.2034-2040, 2006. ,
DOI : 10.1016/j.jmva.2006.03.007