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Integration in a dynamical stochastic geometric framework

Giacomo Aletti, Enea G. Bongiorno, Vincenzo Capasso (2011)

ESAIM: Probability and Statistics

Motivated by the well-posedness of birth-and-growth processes, a stochastic geometric differential equation and, hence, a stochastic geometric dynamical system are proposed. In fact, a birth-and-growth process can be rigorously modeled as a suitable combination, involving the Minkowski sum and the Aumann integral, of two very general set-valued processes representing nucleation and growth dynamics, respectively. The simplicity of the proposed geometric approach allows to avoid problems of boundary...

Integration in a dynamical stochastic geometric framework

Giacomo Aletti, Enea G. Bongiorno, Vincenzo Capasso (2012)

ESAIM: Probability and Statistics

Motivated by the well-posedness of birth-and-growth processes, a stochastic geometric differential equation and, hence, a stochastic geometric dynamical system are proposed. In fact, a birth-and-growth process can be rigorously modeled as a suitable combination, involving the Minkowski sum and the Aumann integral, of two very general set-valued processes representing nucleation and growth dynamics, respectively. The simplicity of the proposed geometric approach allows to avoid problems of boundary...

Kolmogorov equation and large-time behaviour for fractional Brownian motion driven linear SDE's

Michal Vyoral (2005)

Applications of Mathematics

We consider a stochastic process X t x which solves an equation d X t x = A X t x d t + Φ d B t H , X 0 x = x where A and Φ are real matrices and B H is a fractional Brownian motion with Hurst parameter H ( 1 / 2 , 1 ) . The Kolmogorov backward equation for the function u ( t , x ) = 𝔼 f ( X t x ) is derived and exponential convergence of probability distributions of solutions to the limit measure is established.

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