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Gaussian processes and neuronal modeling

Contributo in Atti di convegno
Data di Pubblicazione:
2005
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 concerning neuronal activity modeling, 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. Significant similarities or diversities between computational and simulated results are pointed out.
Tipologia CRIS:
04A-Conference paper in volume
Keywords:
neuronal model; gaussian process
Elenco autori:
E. DI NARDO; A. NOBILE; E. PIROZZI; L.M. RICCIARDI
Autori di Ateneo:
DI NARDO Elvira
Link alla scheda completa:
https://iris.unito.it/handle/2318/1561370
Titolo del libro:
Computer Aided Systems Theory - EUROCAST 2005
Pubblicato in:
LECTURE NOTES IN COMPUTER SCIENCE
Journal
LECTURE NOTES IN COMPUTER SCIENCE
Series
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URL

http://www.springerlink.com/content/xdu2gqrne574wg6n/
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