Un nouveau principe de grandes déviations en théorie du filtrage non linéaire
Un problema di controllo stocastico per lo sfruttamento di una risorsa rinnovabile
Un problème de contrôle géométrique et les équations de Hamilton-Jacobi-Bellman
Unbiased minimum-variance filter for state and fault estimation of linear time-varying systems with unknown disturbances.
Unicité des lois optimales du contrôle stochastique continu dans le cas complètement observable
Uniform exponential stability for linear discrete time systems with stochastic perturbations in Hilbert spaces
In this paper we study the exponential and uniform exponential stability problem for linear discrete time-varying systems with independent stochastic perturbations. We give two representations of the solutions of the discussed systems and we use them to obtain necessary and sufficient conditions for the two types of stability. A deterministic characterization of the uniform exponential stability, in terms of Lyapunov equations are given.
Unifying approach to observer-filter design
The paper examines similarities between observer design as introduced in Automatic Control Theory and filter design as established in Signal Processing. It is shown in the paper that there are obvious connections between them in spite of different aims for their design. Therefore, it is prospective to make them be compatible from the structural point of view. Introduced error invariance and error convergence properties of both of them are unifying tools for their design. Lyapunov's stability theory,...
Uniqueness and approximate computation of optimal incomplete transportation plans
For α∈(0, 1) an α-trimming, P∗, of a probability P is a new probability obtained by re-weighting the probability of any Borel set, B, according to a positive weight function, f≤1/(1−α), in the way P∗(B)=∫Bf(x)P(dx). If P, Q are probability measures on euclidean space, we consider the problem of obtaining the best L2-Wasserstein approximation between: (a) a fixed probability and trimmed versions of the other; (b) trimmed versions of both probabilities. These best trimmed approximations naturally...
Uniqueness of optimal policies as a generic property of discounted Markov decision processes: Ekeland's variational principle approach
Many examples in optimization, ranging from Linear Programming to Markov Decision Processes (MDPs), present more than one optimal solution. The study of this non-uniqueness is of great mathematical interest. In this paper the authors show that in a specific family of discounted MDPs, non-uniqueness is a “fragile” property through Ekeland's Principle for each problem with at least two optimal policies; a perturbed model is produced with a unique optimal policy. This result not only supersedes previous...
Unscented filtering from delayed observations with correlated noises.
Utilisation de l'algorithme de Kalman pour le traitement des séries chronologiques