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20192022
most citedInhibition enhances the coherence in the Jacobi neuronal model

10 citations · 11 across the 6 of their papers we have counts for

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math.PR2022★ 1 cited

Approximating the first passage time density from data using generalized Laguerre polynomials

Elvira Di Nardo, Giuseppe D'Onofrio, Tommaso Martini

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…

math.PR2022

Jacobi processes with jumps as neuronal models: a first passage time analysis

Giuseppe D'Onofrio, Pierre Patie, Laura Sacerdote

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 descr…

math.PR2021

Deterministic control of SDEs with stochastic drift and multiplicative noise: a variational approach

Giacomo Ascione, Giuseppe D'Onofrio

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 solve…

math.PR2020

A cumulant approach for the first-passage-time problem of the Feller square-root process

Elvira Di Nardo, Giuseppe D'Onofrio

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 appro…

math.PR2019

An Optimal Gauss-Markov Approximation for a Process with Stochastic Drift and Applications

Giacomo Ascione, Giuseppe D'Onofrio, Lubomir Kostal +1

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…