Simulations of Gaussian Processes and Neuronal Modeling
Abstract
The research work outlined in the present note highlights the essential role played by the simulation procedures implemented by us on CINECA supercomputers to complement the mathematical investigations carried within our group over the past several years. The ultimate target of our research is the understanding of certain crucial features of the information processing and transmission by single neurons embedded in complex networks. More specifically, here we provide a bird's eye look of some analytical, numerical and simulation results on the asymptotic behavior of first passage time densities for Gaussian processes, both of a Markov and of a non-Markov type. Several figures indicate significant similarities or diversities between computational and simulated results.
Cite
@article{arxiv.math/0412035,
title = {Simulations of Gaussian Processes and Neuronal Modeling},
author = {Elvira Di Nardo and Amelia G. Nobile and Enrica Pirozzi and Luigi M. Ricciardi},
journal= {arXiv preprint arXiv:math/0412035},
year = {2007}
}
Comments
Extended version of the paper published in Science and Supercomputing at CINECA - Report 2003 (Garofalo F., Moretti M., Voli M., eds.), 375-381. ISBN 88-86037-13-9