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Title: Auto-associative nanoelectronic neural network

In this paper, an auto-associative neural network using single-electron tunneling (SET) devices is proposed and simulated at low temperature. The nanoelectronic auto-associative network is able to converge to a stable state, previously stored during training. The recognition of the pattern involves decreasing the energy of the input state until it achieves a point of local minimum energy, which corresponds to one of the stored patterns.
Authors:
;  [1]
  1. Departamento de Engenharia Elétrica - Laboratório de Dispositivos e Circuito Integrado, Universidade de Brasília, CP 4386, CEP 70904-970 Brasília DF (Brazil)
Publication Date:
OSTI Identifier:
22280310
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1598; Journal Issue: 1; Conference: LDSD 2011: 7. international conference on low dimensional structures and devices, Telchac (Mexico), 22-27 May 2011; Other Information: (c) 2014 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
77 NANOSCIENCE AND NANOTECHNOLOGY; COMPUTERIZED SIMULATION; ELECTRONS; NANOSTRUCTURES; NEURAL NETWORKS; TEMPERATURE DEPENDENCE; TUNNEL EFFECT