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Deterministic constructions for sparse regression
In this thesis we investigate some deterministic designs for the sparse regression. Our issue is mainly inspired by Compressed Sensing which is concerned by... -
Sparse Binary Matrices of LDPC codes for Compressed Sensing
Document correspondant à la page publiée dans les actes de la conférence -
On the Achievability of Cramér-Rao Bound in Noisy Compressed Sensing
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Blind Calibration For Compressed Sensing By Convex Optimization
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Sparse underwater acoustic imaging: a case study
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Flexible video coding by combination of a smart decoder and an optimisation r...
This Ph.D. thesis deals with the improvement of video compression efficiency. Both conventional and breakthrough approaches are investigated in order to propose efficient... -
Tractography via the Ensemble Average Propagator in diffusion MRI
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Parametric dictionary learning for modeling EAP and ODF in diffusion MRI
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Blind Spectrum Detector for Cognitive Radio Using Compressed Sensing and Symm...
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On the Use of the Sparse Property of the Cyclic Autocorrelation Function to B...
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VARIANTES SUR UN THÉORÈME DE CANDÈS, ROMBERG ET TAO
A paraître aux Annales de l'Institut Fourier en 2013 -
Hidden cliques and the certification of the restricted isometry property
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Plate impulse response spatial interpolation with sub-Nyquist sampling
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Compressively sampling the plenacoustic function
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Efficiently Decodable Compressed Sensing by List-Recoverable Codes and Recursion
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Compressible Distributions for High-dimensional Statistics
Was previously entitled "Compressible priors for high-dimensional statistics" -
The Cosparse Analysis Model and Algorithms
Preprint available on arXiv since 24 Jun 2011 -
JOINT TRACE/TV NORM MINIMIZATION: A NEW EFFICIENT APPROACH FOR SPECTRAL COMPR...
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HYPERSPECTRAL IMAGE COMPRESSED SENSING VIA LOW-RANK AND JOINT-SPARSE MATRIX R...
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Rank Awareness in Joint Sparse Recovery
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