Learning sparse messages in networks of neural cliques, IEEE Trans. Neural Networks, 2012. ,
Neural correlations, population coding and computation, Nature Reviews Neuroscience, vol.2, issue.5, pp.358-366, 2006. ,
DOI : 10.1038/nrn1888
Information theory, complexity and neural networks, IEEE Communications Magazine, vol.27, issue.11, pp.25-28, 1989. ,
DOI : 10.1109/35.41397
Human memory: A proposed system and its control processes, Psychology of Learning and Motivation, pp.89-195, 1968. ,
Information Theoretic Bounds for Compressed Sensing, IEEE Transactions on Information Theory, vol.56, issue.10, pp.5111-5130, 2010. ,
DOI : 10.1109/TIT.2010.2059891
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
Compressive Sampling [From the Guest Editors], IEEE Signal Processing Magazine, vol.25, issue.2, pp.12-13, 2008. ,
DOI : 10.1109/MSP.2008.915557
Universal MAP estimation in compressed sensing, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2011. ,
DOI : 10.1109/Allerton.2011.6120245
Speeded-up robust features (SURF), Computer Vision and Image Understanding (CVIU), vol.110, issue.3, pp.346-359, 2008. ,
Near optimum error correcting coding and decoding: turbo-codes, IEEE Transactions on Communications, vol.44, issue.10, pp.1261-1271, 1996. ,
DOI : 10.1109/26.539767
Working memory The psychology of learning and motivation, volume VIII, pp.47-89 ,
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
Information theory and neural coding, Nature Neuroscience, vol.2, issue.11, pp.947-957, 1999. ,
DOI : 10.1038/14731
Compressive sampling, Proc. of the International Congress of Mathematicians, 2006. ,
The restricted isometry property and its implications for compressed sensing Compte Rendus de l, Academie des Sciences, Serie I, issue.346, pp.589-592, 2008. ,
A statistically based density map method for identification and quantification of regional differences in microcolumnarity in the monkey brain, Journal of Neuroscience Methods, vol.141, issue.2, pp.321-332, 2005. ,
DOI : 10.1016/j.jneumeth.2004.09.005
Error correction via linear programming, 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05), pp.295-308, 2005. ,
DOI : 10.1109/SFCS.2005.5464411
Decoding by Linear Programming, IEEE Transactions on Information Theory, vol.51, issue.12, pp.4203-4215, 2005. ,
DOI : 10.1109/TIT.2005.858979
Elements of Information Theory, 2006. ,
An Introduction To Compressive Sampling, IEEE Signal Processing Magazine, vol.25, issue.2, pp.21-30, 2008. ,
DOI : 10.1109/MSP.2007.914731
Testing the nullspace property using semidefinite programming, Math. Progr, 2010. ,
Testing the nullspace property using semidefinite programming, Mathematical Programming, pp.123-144, 2011. ,
Message-passing algorithms for compressed sensing, 2009. 122 BIBLIOGRAPHY [Don06] D. L. Donoho. Compressed sensing, pp.1289-1306, 2006. ,
DOI : 10.1073/pnas.0909892106
Complex dynamics in winner-take-all neural nets with slow inhibition, Neural Networks, vol.5, issue.3, pp.415-431, 1992. ,
Necessary and Sufficient Conditions for Sparsity Pattern Recovery, IEEE Transactions on Information Theory, vol.55, issue.12, pp.555758-5772, 2009. ,
DOI : 10.1109/TIT.2009.2032726
The rank of a random matrix, Applied Mathematics and Computation, vol.185, issue.1, pp.689-694, 2007. ,
DOI : 10.1016/j.amc.2006.07.076
Low-density parity-check codes, IEEE Trans. Inf. Theory, vol.8, issue.1, pp.21-28, 1962. ,
Sparse Neural Networks With Large Learning Diversity, IEEE Transactions on Neural Networks, vol.22, issue.7, pp.1087-1096, 2011. ,
DOI : 10.1109/TNN.2011.2146789
URL : https://hal.archives-ouvertes.fr/hal-00609246
Nearly-optimal associative memories based on distributed constant weight codes, 2012 Information Theory and Applications Workshop, pp.269-273, 2012. ,
DOI : 10.1109/ITA.2012.6181790
URL : https://hal.archives-ouvertes.fr/hal-01056531
Toeplitz and Circulant Matrices: A Review, 2006. ,
Does the huamn mnid raed wrods as a wlohe?, Trends in Cognitive Sciences, vol.8, issue.2, pp.58-59, 2004. ,
DOI : 10.1016/j.tics.2003.11.006
URL : https://hal.archives-ouvertes.fr/hal-01441314
A mathematical theory of communication, Bell System Technical Journal, vol.29, pp.147-160, 1950. ,
Statistical Digital Signal Processing and Modeling, 1996. ,
Neural Networks: A Comprehensive Foundation, 1999. ,
Adaptive Filter Theory, 2001. ,
Cognitive radio: brain-empowered wireless communications, IEEE J. Sel. Areas in Commun, vol.23, issue.2, pp.201-220, 2005. ,
Communication Systems, 2009. ,
Fighting the curse of dimensionality: Compressive sensing in exploration seismology, IEEE Signal Processing Magazine, vol.29, issue.3, pp.88-100 ,
Cognitive radio: making software radios more personal, IEEE Personal Communications, vol.6, issue.4, pp.13-18, 1999. ,
DOI : 10.1109/98.788210
Tight lower bounds on the ergodic capacity of ricean fading MIMO channels, Proc. IEEE International Conference on Communications (ICC), pp.2412-2416, 2005. ,
Limits on Support Recovery of Sparse Signals via Multiple-Access Communication Techniques, IEEE Transactions on Information Theory, vol.57, issue.12, pp.7877-7892, 2011. ,
DOI : 10.1109/TIT.2011.2170116
Minimum complexity pursuit: Stability analysis, 2012 IEEE International Symposium on Information Theory Proceedings, 2012. ,
DOI : 10.1109/ISIT.2012.6283602
URL : http://arxiv.org/abs/1205.4673
Error Control Coding, pp.49-60, 1988. ,
Compressed Sensing MRI, IEEE Signal Processing Magazine, vol.25, issue.2, pp.72-82, 2008. ,
DOI : 10.1109/MSP.2007.914728
Deterministic Construction of Compressed Sensing Matrices via Algebraic Curves, IEEE Transactions on Information Theory, vol.58, issue.8, pp.5035-5041, 2012. ,
DOI : 10.1109/TIT.2012.2196256
An introduction to factor graphs, IEEE Signal Processing Magazine, vol.21, issue.1, pp.28-41, 2004. ,
Object recognition from local scale-invariant features, Proc. Seventh IEEE Int. Conf. on Computer Vision, pp.1150-1157, 1999. ,
On the computational power of winner-take-all, Neural Computation, vol.12, issue.11, pp.2519-2535, 2000. ,
Matrix Analysis and Applied Linear Algebra, 2001. ,
The magical number seven, plus or minus two: some limits on our capacity for processing information, Psychological Review, vol.63, issue.2, pp.81-97, 1956. ,
On cliques in graphs, Israel Journal of Mathematics, vol.3, issue.1, pp.23-28, 1965. ,
DOI : 10.1007/BF02760024
The columnar organization of the neocortex, Brain : a journal of neurology, vol.120, issue.4, pp.701-722, 1997. ,
A logical calculus of the ideas immanent in nervous activity, Bulletin of Mathematical Biology, vol.5, issue.4, pp.115-133, 1943. ,
Bounds for eigenvalues using the trace and determinant, Linear Algebra and its Applications, vol.264, pp.101-108, 1997. ,
DOI : 10.1016/S0024-3795(97)00067-0
Tight lower bounds on the ergodic capacity of Rayleigh fading MIMO channels, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE, pp.1172-1176, 2002. ,
DOI : 10.1109/GLOCOM.2002.1188380
The Brain Might Read That Way, Scientific Studies of Reading, vol.47, issue.3, pp.293-304, 2004. ,
DOI : 10.1037//0022-0663.91.3.415
Nearly sharp sufficient conditions on exact sparsity pattern recovery, IEEE Trans. Inf. Theory, vol.57, issue.7, pp.4672-4679, 2011. ,
Modern Coding Theory, 2008. ,
DOI : 10.1017/CBO9780511791338
Bayesian Attractor Neural Network Models of Memory ,
Measurements vs. bits: Compressed sensing meets information theory, Proc. 44th Annual Allerton Conf. on Commun., Control, and Computing, pp.126-132, 2003. ,
A mathematical theory of communication, Bell System Technical Journal, vol.27, 1948. ,
Iterative retrieval of sparsely coded associative memory patterns, Neural Networks, vol.9, issue.3, 1996. ,
DOI : 10.1016/0893-6080(95)00112-3
Explicit thresholds for approximately sparse compressed sensing via ? 1 -optimization, Proc. IEEE Int. Symp. Inf. Theory (ISIT), pp.478-482, 2009. ,
Bayesian compressive sensing, IEEE Trans. Signal Processing, vol.56, issue.6, pp.2346-2356, 2008. ,
Compressed sensing of autoregressive processes, Wavelets XIII, 2009. ,
DOI : 10.1117/12.826830
Segmented Compressed Sampling for Analog-to-Information Conversion: Method and Performance Analysis, IEEE Transactions on Signal Processing, vol.59, issue.2 ,
DOI : 10.1109/TSP.2010.2091411
The brain of a new machine, IEEE Spectrum, vol.47, issue.12, p.47, 2010. ,
DOI : 10.1109/MSPEC.2010.5644776
Information-theoretic limits on sparsity recovery in the high-dimensional and noisy setting, IEEE Trans. Inf. Theory, vol.55, issue.12, pp.5728-5741, 2009. ,
Learning compressed sensing, Proc. 45th Annual Allerton Conf. on Commun., Control, and Computing, 2007. ,
Discovering the capacity of human memory, Brain and Mind, vol.4, issue.2, pp.189-198, 2003. ,
DOI : 10.1023/A:1025405628479
Information-Theoretic Limits on Sparse Signal Recovery: Dense versus Sparse Measurement Matrices, IEEE Transactions on Information Theory, vol.56, issue.6, pp.2967-2979, 2010. ,
DOI : 10.1109/TIT.2010.2046199
On the log determinant of noncentral wishart matrices, Proc. IEEE Int. Symp. Inf. Theory (ISIT) ,
Linear transformations and Restricted Isometry Property, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.2961-2964, 2009. ,
DOI : 10.1109/ICASSP.2009.4960245
URL : http://arxiv.org/abs/0901.0541
On compressed blind de-convolution of filtered sparse processes, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.4038-4041, 2010. ,
DOI : 10.1109/ICASSP.2010.5495759