Published June 1996
| Version v1
Journal article
Robustness against S.E.U. of an artificial neural network space application
- 1. IMAG, Grenoble (France). Lab. de Genie Informatique
- 2. CNRS, Orleans (France). Lab. de Physique et Chimie d l'Environnement
- 3. Centre National d'Etudes Spatiales, Toulouse (France)
Description
The authors study the sensitivity of Artificial Neural Networks (ANN) to Single Event Upsets (SEU). A neural network designed to detect electronic and protonic whistlers has been implemented using a dedicated VLSI circuit: the LNeuro neural processor. Results of both SEU software simulations and heavy ion tests point out the fault tolerance properties of ANN hardware implementations
Additional details
Publishing Information
- Journal Title
- IEEE Transactions on Nuclear Science
- Journal Volume
- 43
- Journal Issue
- 3Pt1
- Journal Page Range
- p. 973-978.
- ISSN
- 0018-9499
- CODEN
- IETNAE
Conference
- Title
- 3. European symposium on radiations and their effects on components and systems.
- Dates
- 18-22 Sep 1995.
- Place
- Arcachon (France).
INIS
- Country of Publication
- United States
- Country of Input or Organization
- United States
- INIS RN
- 27075943
- Subject category
- S46: INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY;
- Resource subtype / Literary indicator
- Conference, Numerical Data
- Descriptors DEI
- COMPUTERIZED SIMULATION; ERRORS; EXPERIMENTAL DATA; INTEGRATED CIRCUITS; IONIZING RADIATIONS; NEURAL NETWORKS; PHYSICAL RADIATION EFFECTS; SPACE FLIGHT; THEORETICAL DATA
- Descriptors DEC
- DATA; ELECTRONIC CIRCUITS; INFORMATION; NUMERICAL DATA; RADIATION EFFECTS; RADIATIONS; SIMULATION
Optional Information
- Secondary number(s)
- CONF-9509107--.