Endogenous noise has been shown to play a central role in the detection of an electromagnetic signal in the nervous system. In this work, following a biomedical perspective, an exogenous noise applied to a realistic feedforward network model has been considered. It will be shown that, if the exogenous noise is properly filtered and its level is adjusted, a clear optimization of network encoding of an electromagnetic signal, representative of an external stimulation, is obtained through the stochastic resonance paradigm.
Effects of an exogenous noise on a realistic network model: Encoding of an EM signal / Paffi, Alessandra; M., Gianni; Maggio, Fernando; Liberti, Micaela; Apollonio, Francesca; D'Inzeo, Guglielmo. - 2007:(2007), pp. 2404-2407. (Intervento presentato al convegno 29th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society tenutosi a Lyon, FRANCE nel AUG 22-26, 2007) [10.1109/iembs.2007.4352812].
Effects of an exogenous noise on a realistic network model: Encoding of an EM signal
PAFFI, ALESSANDRA;MAGGIO, FERNANDO;LIBERTI, Micaela;APOLLONIO, Francesca;D'INZEO, Guglielmo
2007
Abstract
Endogenous noise has been shown to play a central role in the detection of an electromagnetic signal in the nervous system. In this work, following a biomedical perspective, an exogenous noise applied to a realistic feedforward network model has been considered. It will be shown that, if the exogenous noise is properly filtered and its level is adjusted, a clear optimization of network encoding of an electromagnetic signal, representative of an external stimulation, is obtained through the stochastic resonance paradigm.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
