DocumentCode
1095336
Title
Robustness against SEU of an artificial neural network space application
Author
Assoum, A. ; Radi, N.E. ; Velazco, R. ; Elie, F. ; Ecoffet, R.
Author_Institution
Lab. de Genie Inf., IMAG, Grenoble, France
Volume
43
Issue
3
fYear
1996
fDate
6/1/1996 12:00:00 AM
Firstpage
973
Lastpage
978
Abstract
We 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
Keywords
VLSI; aerospace computing; errors; fault tolerant computing; ion beam effects; neural chips; special purpose computers; whistlers; LNeuro neural processor; SEU robustness; artificial neural network; dedicated VLSI circuit; electronic whistler detection; fault tolerance; heavy ion testing; protonic whistler detection; single event upsets; software simulation; space application; Artificial neural networks; Fault tolerance; Hardware; Neural networks; Neurons; Noise robustness; Satellites; Signal processing algorithms; Single event upset; Very large scale integration;
fLanguage
English
Journal_Title
Nuclear Science, IEEE Transactions on
Publisher
ieee
ISSN
0018-9499
Type
jour
DOI
10.1109/23.510742
Filename
510742
Link To Document