Published February 2006 | Version v1
Journal article

Neuronal synchrony detection on single-electron neural networks

  • 1. Department of Electrical Engineering, Hokkaido University, Kita 13, Nishi 8, Sapporo 060-8628 (Japan)

Description

Synchrony detection between burst and non-burst spikes is known to be one functional example of depressing synapses. Kanazawa et al. demonstrated synchrony detection with MOS depressing synapse circuits. They found that the performance of a network with depressing synapses that discriminates between burst and random input spikes increases non-monotonically as the static device mismatch is increased. We designed a single-electron depressing synapse and constructed the same network as in Kanazawa's study to develop noise-tolerant single-electron circuits. We examined the temperature characteristics and explored possible architecture that enables single-electron circuits to operate at T > 0 K

Additional details

Identifiers

DOI
10.1016/j.chaos.2005.04.059;
PII
S0960-0779(05)00382-6;

Publishing Information

Journal Title
Chaos, Solitons and Fractals
Journal Volume
27
Journal Issue
4
Journal Page Range
p. 887-894
ISSN
0960-0779

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
37003538
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
DETECTION; ELECTRONS; NEURAL NETWORKS; NOISE; PERFORMANCE; RANDOMNESS; TEMPERATURE RANGE 0000-0013 K
Descriptors DEC
ELEMENTARY PARTICLES; FERMIONS; LEPTONS; TEMPERATURE RANGE

Optional Information

Copyright
Copyright (c) 2005 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.