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.