Quantum dissipation and neural net dynamics
Quantum Physics
2007-05-23 v1 Other Condensed Matter
High Energy Physics - Theory
Biological Physics
Other Quantitative Biology
Abstract
Inspired 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.
Cite
@article{arxiv.quant-ph/9912070,
title = {Quantum dissipation and neural net dynamics},
author = {Eliano Pessa and Giuseppe Vitiello},
journal= {arXiv preprint arXiv:quant-ph/9912070},
year = {2007}
}
Comments
latex file Published: Bioelectrochemistry and Bioenergetics, 48:339-342, 1999