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Nash Equilibria in a class of Markov stopping games

Rolando Cavazos-Cadena, Daniel Hernández-Hernández (2012)

Kybernetika

This work concerns a class of discrete-time, zero-sum games with two players and Markov transitions on a denumerable space. At each decision time player II can stop the system paying a terminal reward to player I and, if the system is no halted, player I selects an action to drive the system and receives a running reward from player II. Measuring the performance of a pair of decision strategies by the total expected discounted reward, under standard continuity-compactness conditions it is shown...

Natural divisors and the brownian motion

Eugenijus Manstavičius (1996)

Journal de théorie des nombres de Bordeaux

A model of the Brownian motion defined in terms of the natural divisors is proposed and weak convergence of the related measures in the space 𝐃 [0,1] is proved. An analogon of the Erdös arcsine law, known for the prime divisors [6] (see [14] for the proof), is obtained. These results together with the author’s investigation [15] extend the systematic study [9] of the distribution of natural divisors. Our approach is based upon the functional limit theorems of probability theory.

Nevanlinna theory, Fuchsian functions and Brownian motion windings.

Jean-Claude Gruet (2002)

Revista Matemática Iberoamericana

Atsuji proposed some integrals along Brownian paths to study the Nevanlinna characteristic function T(f,r) when f is meromorphic in the unit disk D. We show that his criterios does not apply to the basic case when f is a modular elliptic function. The divergence of similar integrals computed along the geodesic flow is also proved. (A)

Non-fragile sampled data H ∞ filtering of general continuous Markov jump linear systems

Mouquan Shen, Guangming Zhang, Yuhao Yuan, Lei Mei (2014)

Kybernetika

This paper is concerned with the non-fragile sampled data H ∞ filtering problem for continuous Markov jump linear system with partly known transition probabilities (TPs). The filter gain is assumed to have additive variations and TPs are assumed to be known, uncertain with known bounds and completely unknown. The aim is to design a non-fragile H ∞ filter to ensure both the robust stochastic stability and a prescribed level of H ∞ performance for the filtering error dynamics. Sufficient conditions for...

Nonlinear filtering for Markov systems with delayed observations

Antonella Calzolari, Patrick Florchinger, Giovanna Nappo (2009)

International Journal of Applied Mathematics and Computer Science

This paper deals with nonlinear filtering problems with delays, i.e., we consider a system (X,Y), which can be represented by means of a system (X,Ŷ), in the sense that Yt = Ŷa(t), where a(t) is a delayed time transformation. We start with X being a Markov process, and then study Markovian systems, not necessarily diffusive, with correlated noises. The interest is focused on the existence of explicit representations of the corresponding filters as functionals depending on the observed trajectory....

Nonlinear filtering for observations on a random vector field along a random path. Application to atmospheric turbulent velocities

Christophe Baehr (2010)

ESAIM: Mathematical Modelling and Numerical Analysis

To filter perturbed local measurements on a random medium, a dynamic model jointly with an observation transfer equation are needed. Some media given by PDE could have a local probabilistic representation by a Lagrangian stochastic process with mean-field interactions. In this case, we define the acquisition process of locally homogeneous medium along a random path by a Lagrangian Markov process conditioned to be in a domain following the path and conditioned to the observations. The nonlinear...

Nonlinear Markov processes in big networks

Quan-Lin Li (2016)

Special Matrices

Big networks express multiple classes of large-scale networks in many practical areas such as computer networks, internet of things, cloud computation, manufacturing systems, transportation networks, and healthcare systems. This paper analyzes such big networks, and applies the mean-field theory and the nonlinear Markov processes to constructing a broad class of nonlinear continuous-time block-structured Markov processes, which can be used to deal with many practical stochastic systems. Firstly,...

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