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
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 Kalman filtering using the limited memory BFGS method.
Le problème de Cauchy pour les équations de Hamilton-Jacobi-Bellman
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
Limiting average cost control problems in a class of discrete-time stochastic systems
We consider a class of -valued stochastic control systems, with possibly unbounded costs. The systems evolve according to a discrete-time equation (t = 0,1,... ), for each fixed n = 0,1,..., where the are i.i.d. random vectors, and the Gₙ are given functions converging pointwise to some function as n → ∞. Under suitable hypotheses, our main results state the existence of stationary control policies that are expected average cost (EAC) optimal and sample path average cost (SPAC) optimal for...
Linear discrete-time systems with Markovian jumps and mode dependent time-delay: stability and stabilizability.
Linear filtering of systems with memory and application to finance.
Linear filtering with fractional Brownian motion in the signal and observation processes.
Linear prediction: Mathematics and engineering.
Linear quadratic control. State space vs. polynomial equations
LMI optimization problem of delay-dependent robust stability criteria for stochastic systems with polytopic and linear fractional uncertainties
This paper studies an LMI optimization problem of delay-dependent robust stability criteria for stochastic systems with polytopic and linear fractional uncertainties. The delay is assumed to be time-varying and belong to a given interval, which means that lower and upper bounds of this interval time-varying delay are available. The uncertainty under consideration includes polytopic-type uncertainty and linear fractional norm-bounded uncertainty. Based on the new Lyapunov-Krasovskii functional, some...
LMS-Newton adaptive filtering using FFT-based conjugate gradient iterations.
Local detection of defects from image sequences
Our aim is to discuss three approaches to the detection of defects in continuous production processes, which are based on local methods of processing image sequences. These approaches are motivated by and applicable to images of hot metals or other surfaces, which are uniform at a macroscopic level, when defects are not present. The first of them is based on the estimation of fractal dimensions of image cross-sections. The second and third approaches are compositions of known techniques, which are...
LPV design of fault-tolerant control for road vehicles
The aim of the paper is to present a supervisory decentralized architecture for the design and development of reconfigurable and fault-tolerant control systems in road vehicles. The performance specifications are guaranteed by local controllers, while the coordination of these components is provided by a supervisor. Since the monitoring components and FDI filters provide the supervisor with information about the various vehicle maneuvers and the different fault operations, it is able to make decisions...