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Digital image analysis appears to be more and more relevant to the study of physical phenomena involving uid motion, and of their evolution over time. In that context, 2D deformable motion analysis is one of the most important issues to be investigated. The interpretation of such deformable 2D ow elds can generally be stated as the characterization of… (More)
We discuss new methods for the recovery of signals with block-sparse structure, based on 1-minimization. Our emphasis is on the efficiently computable error bounds for the recovery routines. We optimize these bounds with respect to the method parameters to construct the estimators with improved statistical properties. We justify the proposed approach with… (More)
We propose new methods for estimating the frontier of a set of points. The estimates are defined as kernel functions covering all the points and whose associated support is of smallest surface. They are written as linear combinations of kernel functions applied to the points of the sample. The weights of the linear combination are then computed by solving a… (More)
We prove the central limit theorem for stochastic approximation when the Polyak-Ruppert averaging method is utilized Le th eor eme-limite central pour l'approximation stochastique avec moyennisation R esum e : On d emontre la convergence de la m ethode de moyennisation de Polyak-Ruppert sous des hypoth eses raisonnables.
This thesis presents a study of polynomial dynamical systems motivated by both the wide spectrum of applications of this class (chemical reaction models, electrical models and biological models) and the difficulty (or inability) of theoretical resolution of such systems. In a first preliminary part, we present multivariate polynomials and we introduce the… (More)