Quantum dissipation and neural net dynamics

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dc.creatorPessa, Eliano
dc.creatorVitiello, Giuseppe
dc.date1999-12-14
dc.date.accessioned2026-07-07T06:17:21Z
dc.date.available2026-07-07T06:17:21Z
dc.descriptionInspired by the dissipative quantum model of brain, we model the states of neural nets in terms of collective modes by the help of the formalism of Quantum Field Theory. We exhibit an explicit neural net model which allows to memorize a sequence of several informations without reciprocal destructive interference, namely we solve the overprinting problem in such a way last registered information does not destroy the ones previously registered. Moreover, the net is able to recall not only the last registered information in the sequence, but also anyone of those previously registered.
dc.descriptionlatex file Published: Bioelectrochemistry and Bioenergetics, 48:339-342, 1999
dc.identifierhttps://arxiv.org/abs/quant-ph/9912070
dc.identifierhttp://arxiv.org/abs/quant-ph/9912070
dc.identifierBioelectrochem.Bioenerg 48 (1999) 339-342
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/94362
dc.subjectQuantum Physics
dc.subjectOther Condensed Matter
dc.subjectHigh Energy Physics - Theory
dc.subjectBiological Physics
dc.subjectOther Quantitative Biology
dc.titleQuantum dissipation and neural net dynamics
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