DocumentCode
1310597
Title
Artificial neural network robustness for on-board satellite image processing: results of upset simulations and ground tests
Author
Velazco, R. ; Cheynet, P.H. ; Muller, J.D. ; Ecoffet, R. ; Buchner, S.
Author_Institution
Lab. Logiciels, Syst., Reseaux, IMAG, Grenoble, France
Volume
44
Issue
6
fYear
1997
fDate
12/1/1997 12:00:00 AM
Firstpage
2337
Lastpage
2344
Abstract
Artificial Neural Networks have been shown to possess fault tolerant properties. We present the architecture of a neural network designed to process satellite images (SPOT photos). Computer simulations and ground tests performed on a digital implementation of this neural network prove its robustness with respect to bit errors
Keywords
digital integrated circuits; image texture; integrated circuit testing; neural chips; radiation effects; space vehicle electronics; SPOT photos; artificial neural network robustness; bit errors; fault tolerant properties; ground tests; on-board satellite image processing; upset simulations; Artificial neural networks; Artificial satellites; Computer architecture; Computer errors; Computer simulation; Fault tolerance; Performance evaluation; Process design; Robustness; Testing;
fLanguage
English
Journal_Title
Nuclear Science, IEEE Transactions on
Publisher
ieee
ISSN
0018-9499
Type
jour
DOI
10.1109/23.659057
Filename
659057
Link To Document