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A distributional equation as a criterion for invariant measures of Markov processes associated to L\'evy-type operators is established. This is obtained via a characterization of infinitesimally invariant measures of the associated…

Probability · Mathematics 2022-08-17 Anita Behme , David Oechsler

This paper introduces a novel methodology for the identification of switching dynamics for switched autoregressive linear models. Switching behavior is assumed to follow a Markov model. The system's outputs are contaminated by possibly…

Signal Processing · Electrical Eng. & Systems 2019-03-28 Sarah Hojjatinia , Constantino M. Lagoa

We consider Markov processes of cubic stochastic (in a fixed sense) matrices which are also called quadratic stochastic process (QSPs). A QSP is a particular case of a continuous-time dynamical system whose states are stochastic cubic…

Probability · Mathematics 2017-06-26 J. M. Casas , M. Ladra , U. A. Rozikov

We analyze multidimensional Markovian integral equations that are formulated with a time-inhomogeneous progressive Markov process that has Borel measurable transition probabilities. In the case of a path-dependent diffusion process, the…

Probability · Mathematics 2021-03-09 Alexander Kalinin

We give upper and lower estimates of densities of convolution semigroups of probability measures under explicit assumptions on the corresponding Levy measure and the Levy--Khinchin exponent. We obtain also estimates of derivatives of…

Probability · Mathematics 2015-06-03 Kamil Kaleta , Paweł Sztonyk

Motivated by entropic optimal transport, time reversal of diffusion processes is revisited. An integration by parts formula is derived for the carr\'e du champ of a Markov process in an abstract space. It leads to a time reversal formula…

Probability · Mathematics 2022-09-05 Patrick Cattiaux , Giovanni Conforti , Ivan Gentil , Christian Léonard

Conditional independence and graphical models are crucial concepts for sparsity and statistical modeling in higher dimensions. For L\'evy processes, a widely applied class of stochastic processes, these notions have not been studied. By the…

Statistics Theory · Mathematics 2024-11-13 Sebastian Engelke , Jevgenijs Ivanovs , Jakob D. Thøstesen

Markov Decision Processes (Mdps) form a versatile framework used to model a wide range of optimization problems. The Mdp model consists of sets of states, actions, time steps, rewards, and probability transitions. When in a given state and…

We study the connection between PDEs and L\'{e}vy processes running with clocks given by time-changed Poisson processes with stochastic drifts. The random times we deal with are therefore given by time-changed Poissonian jumps related to…

Probability · Mathematics 2014-01-15 Luisa Beghin , Mirko D'Ovidio

Markov Decision Processes (MDPs) have been used to formulate many decision-making problems in science and engineering. The objective is to synthesize the best decision (action selection) policies to maximize expected rewards (or minimize…

Optimization and Control · Mathematics 2015-07-07 Mahmoud El Chamie , Behcet Acikmese

In this article we study a class of stochastic functional differential equations driven by L\'{e}vy processes (in particular, $\alpha$-stable processes), and obtain the existence and uniqueness of Markov solutions in small time intervals.…

Probability · Mathematics 2012-11-30 Xicheng Zhang

We aim at characterizing viability, invariance and some reachability properties of controlled piecewise deterministic Markov processes (PDMPs). Using analytical methods from the theory of viscosity solutions, we establish criteria for…

Optimization and Control · Mathematics 2013-04-09 D. Goreac

We introduce G-L\'{e}vy processes which develop the theory of processes with independent and stationary increments under the framework of sublinear expectations. We then obtain the L\'{e}vy-Khintchine formula and the existence for…

Probability · Mathematics 2009-11-19 Mingshang Hu , Shige Peng

This paper deals with the output regulation problem (ORP) of a linear time-invariant (LTI) system in the presence of sporadically sampled measurement streams with the inter-sampling intervals following a stochastic process. Under such…

Systems and Control · Electrical Eng. & Systems 2023-06-28 Himadri Basu , Francesco Ferrante , Mirko Fiacchini

This paper considers the speed of convergence (mixing) of a finite Markov kernel $P$ with respect to the Kullback-Leibler divergence (entropy). Given a Markov kernel one defines either a discrete-time Markov chain (with the $n$-step…

Probability · Mathematics 2024-09-13 Pietro Caputo , Zongchen Chen , Yuzhou Gu , Yury Polyanskiy

This paper deals with control of partially observable discrete-time stochastic systems. It introduces and studies Markov Decision Processes with Incomplete Information and with semi-uniform Feller transition probabilities. The important…

Optimization and Control · Mathematics 2022-08-30 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

We investigate some recursive procedures based on an exact or ``approximate'' Euler scheme with decreasing step in vue to computation of invariant measures of solutions to S.D.E. driven by a L\'evy process. Our results are valid for a large…

Probability · Mathematics 2008-04-02 Fabien Panloup

In this paper, we consider a class of inhomogeneous semi-Markov processes directly based on intensity processes for marked point processes. We show that this class satisfies the semi-Markov properties defined elsewhere in the literature. We…

Probability · Mathematics 2015-04-14 Alexander Sokol

The objective of this paper is to study the filtering problem for a system of partially observable processes $(X, Y)$, where $X$ is a non-Markovian pure-jump process representing the signal and $Y$ is a general jump-diffusion which provides…

Probability · Mathematics 2022-06-02 Elena Bandini , Alessandro Calvia , Katia Colaneri

A classical random walk $(S_t, t\in\mathbb{N})$ is defined by $S_t:=\displaystyle\sum_{n=0}^t X_n$, where $(X_n)$ are i.i.d. When the increments $(X_n)_{n\in\mathbb{N}}$ are a one-order Markov chain, a short memory is introduced in the…

Probability · Mathematics 2012-08-17 Peggy Cénac , Brigitte Chauvin , Samuel Herrmann , Pierre Vallois
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