Distributions sur l'espace de Wiener (suite), d'après Kubo et Yokoi
Distribution-valued iterated gradient and chaotic decompositions of Poisson jump times functionals.
We define a class of distributions on Poisson space which allows to iterate a modification of the gradient of [1]. As an application we obtain, with relatively short calculations, a formula for the chaos expansion of functionals of jump times of the Poisson process.
Distribution-Valued Processes Arising from Independent Brownian Motions.
Distributive laws. Applications to stochastic automata. (Lois distributives. Applications aux automates stochastiques.)
Divergence Processes and Weak Convergence of Likelihood Ratio Processes
Divergences of Gauss-Markov random fields with application to statistical inference
Dobrushin's approach to queueing network theory.
Domain of partial attraction for infinitely divisible distributions in a Hilbert space
Domain perturbations, Brownian motion, capacities, and ground states of Dirichlet Schrödinger operators.
Domains of attraction in Banach spaces
Domains of attraction of stable measures on a Hilbert space
Domains of attraction of the real random vector and applications
Domains of partial attraction in several dimensions
Domination by Borel stopping times and some separation properties
Donsker-type theorem for BSDEs.
Doob's decomposition and Burkholder's inequalities
Doob's type inequality and strong law of large numbers for demimartingales.
Double-barriers-reflected BSDEs with jumps and viscosity solutions of parabolic integrodifferential PDEs.
Double-stepped adaptive control for hybrid systems with unknown Markov jumps and stochastic noises
This paper is concerned with the sampled-data based adaptive linear quadratic (LQ) control of hybrid systems with both unmeasurable Markov jump processes and stochastic noises. By the least matching error estimation algorithm, parameter estimates are presented. By a double-step (DS) sampling approach and the certainty equivalence principle, a sampled-data based adaptive LQ control is designed. The DS-approach is characterized by a comparatively large estimation step for parameter estimation and...
Double-stepped adaptive control for hybrid systems with unknown Markov jumps and stochastic noises
This paper is concerned with the sampled-data based adaptive linear quadratic (LQ) control of hybrid systems with both unmeasurable Markov jump processes and stochastic noises. By the least matching error estimation algorithm, parameter estimates are presented. By a double-step (DS) sampling approach and the certainty equivalence principle, a sampled-data based adaptive LQ control is designed. The DS-approach is characterized by a comparatively large estimation step for parameter estimation and...