Zobrazeno 1 - 10
of 368
pro vyhledávání: '"D'ONOFRIO, GIUSEPPE"'
We consider a discrete-time Markovian random walk with resets on a connected undirected network. The resets, in which the walker is relocated to randomly chosen nodes, are governed by an independent discrete-time renewal process. Some nodes of the ne
Externí odkaz:
http://arxiv.org/abs/2409.08394
We consider three kinds of discrete-time arrival processes: transient, intermediate and recurrent, characterized by a finite, possibly finite and infinite number of events, respectively. In this context, we study renewal processes which are stopped a
Externí odkaz:
http://arxiv.org/abs/2403.06821
In this paper we analyze a method for approximating the first-passage time density and the corresponding distribution function for a CIR process. This approximation is obtained by truncating a series expansion involving the generalized Laguerre polyn
Externí odkaz:
http://arxiv.org/abs/2402.00833
This paper analyzes a method to approximate the first passage time probability density function which turns to be particularly useful if only sample data are available. The method relies on a Laguerre-Gamma polynomial approximation and iteratively lo
Externí odkaz:
http://arxiv.org/abs/2206.02137
To overcome some limits of classical neuronal models, we propose a Markovian generalization of the classical model based on Jacobi processes by introducing downwards jumps to describe the activity of a single neuron. The statistical analysis of inter
Externí odkaz:
http://arxiv.org/abs/2205.08237
Deterministic control of SDEs with stochastic drift and multiplicative noise: a variational approach
Autor:
Ascione, Giacomo, D'Onofrio, Giuseppe
We consider a linear stochastic differential equation with stochastic drift and multiplicative noise. We study the problem of approximating its solution with the process that solves the equation where the possibly stochastic drift is replaced by a de
Externí odkaz:
http://arxiv.org/abs/2110.04010
Autor:
Di Nardo, Elvira, D'Onofrio, Giuseppe
The paper focuses on an approximation of the first passage time probability density function of a Feller stochastic process by using cumulants and a Laguerre-Gamma polynomial approximation. The feasibility of the method relies on closed form formulae
Externí odkaz:
http://arxiv.org/abs/2006.12073
The output signal is examined for the Jacobi neuronal model which is characterized by input-dependent multiplicative noise. The dependence of the noise on the rate of inhibition turns out to be of primary importance to observe maxima both in the outp
Externí odkaz:
http://arxiv.org/abs/1903.10327
We consider a linear stochastic differential equation with stochastic drift. We study the problem of approximating the solution of such equation through an Ornstein-Uhlenbeck type process, by using direct methods of calculus of variations. We show th
Externí odkaz:
http://arxiv.org/abs/1902.09488