-regularity of the boundary to boundary operator for hyperbolic and Petrowski PDEs.
L2 performance induced by feedbacks with multiple saturations
Multi-level saturation feedbacks induce nonlinear disturbance-to-state L2 stability for nonlinear systems in feedforward form. This class of systems includes linear systems with actuator constraints.
La méthode d'approximation de Gauss-Galerkin en filtrage non linéaire
La méthode des semi-martingales en filtrage quand l'observation est un processus ponctuel marqué
Lagrangian formalism in the classical field theory
Large adaptive estimation in linear regression model. I. Consistency
Large deviations principle by viscosity solutions: the case of diffusions with oblique Lipschitz reflections
We establish a Large Deviations Principle for diffusions with Lipschitz continuous oblique reflections on regular domains. The rate functional is given as the value function of a control problem and is proved to be good. The proof is based on a viscosity solution approach. The idea consists in interpreting the probabilities as the solutions to some PDEs, make the logarithmic transform, pass to the limit, and then identify the action functional as the solution of the limiting equation.
Large scale dynamic system stabilization using the principle of dominant subsystems approach
Large variable systems of higher degrees in fuzzification process. Fuzzification of systems for technical and medical practice. II
Large-scale Kalman filtering using the limited memory BFGS method.
Le problème de Cauchy pour les équations de Hamilton-Jacobi-Bellman
Leader-following consensus of multiple linear systems under switching topologies: An averaging method
The leader-following consensus of multiple linear time invariant (LTI) systems under switching topology is considered. The leader-following consensus problem consists of designing for each agent a distributed protocol to make all agents track a leader vehicle, which has the same LTI dynamics as the agents. The interaction topology describing the information exchange of these agents is time-varying. An averaging method is proposed. Unlike the existing results in the literatures which assume the LTI...
Learning extremal regulator implementation by a stochastic automaton and stochastic approximation theory
There exist many different approaches to the investigation of the characteristics of learning system. These approaches use different branches of mathematics and, thus, obtain different results, some of them are too complicated and others do not match the results of practical experiments. This paper presents the modelling of learning systems by means of stochastic automate, mainly one particular model of a learning extremal regulator. The proof of convergence is based on Dvoretzky's Theorem on stochastic...
Learning the naive Bayes classifier with optimization models
Naive Bayes is among the simplest probabilistic classifiers. It often performs surprisingly well in many real world applications, despite the strong assumption that all features are conditionally independent given the class. In the learning process of this classifier with the known structure, class probabilities and conditional probabilities are calculated using training data, and then values of these probabilities are used to classify new observations. In this paper, we introduce three novel optimization...
Least squares in identification theory
L'équation de Zakai et le problème séparé du contrôle optimal stochastique
Less conservative fuzzy control for discrete-time Takagi-Sugeno systems.
Less conservative results for the exponential stability of uncertain time-delay systems
Lie algebroids in classical mechanics and optimal control.
Lie brackets and real analyticity in control theory