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Antonio Di Crescenzo

Researcher at University of Salerno

Publications -  139
Citations -  2316

Antonio Di Crescenzo is an academic researcher from University of Salerno. The author has contributed to research in topics: Stochastic process & Telegraph process. The author has an hindex of 22, co-authored 139 publications receiving 1944 citations. Previous affiliations of Antonio Di Crescenzo include University of Basilicata.

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On a fractional alternating Poisson process

TL;DR: In this paper, a generalization of the alternating Poisson process from the point of view of offractional calculus is proposed, which produces a fractional 2-state point process.
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A multispecies birth–death–immigration process and its diffusion approximation

TL;DR: In this paper, the authors considered an extended birth-death-immigration process defined on a lattice formed by the integers of d semiaxes joined at the origin and investigated the transient and asymptotic behavior of the process via its probability generating function.
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Input-output behaviour of a model neuron with alternating drift

TL;DR: The input-output behaviour of the Wiener neuronal model subject to alternating input is studied and firing densities and related statistics are obtained via simulations of the sample- paths of the process in the following three cases: the drift changes occur during random periods characterised by exponential distribution, Erlang distribution with a preassigned shape parameter, and deterministic distribution.
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A past inaccuracy measure based on the reversed relevation transform

TL;DR: In this paper, an analogue of the Kerridge inaccuracy measure based on the reversed relevation transform is introduced and several results involving equivalent formulas, bounds, monotonicity and stochastic orderings are provided.
Posted Content

Analysis of random walks on a hexagonal lattice

TL;DR: In this article, the authors consider a discrete-time random walk on the nodes of an unbounded hexagonal lattice and determine the probability generating functions, the transition probabilities and the relevant moments.