DocumentCode
1031912
Title
A note on the complexity of reliability in neural networks
Author
Berman, Piotr ; Parberry, Ian ; Schnitger, Georg
Author_Institution
Dept. of Comput. Sci., Pennsylvania State Univ., University Park, PA, USA
Volume
3
Issue
6
fYear
1992
fDate
11/1/1992 12:00:00 AM
Firstpage
998
Lastpage
1002
Abstract
It is shown that in a standard discrete neural network model with small fan-in, tolerance to random malicious faults can be achieved with a log-linear increase in the number of neurons and a constant factor increase in parallel time, provided fan-in can increase arbitrarily. A similar result is obtained for a nonstandard but closely related model with no restriction on fan-in
Keywords
circuit reliability; computational complexity; neural nets; probability; complexity; discrete neural network model; fan-in threshold circuits; fault tolerance; probability; reliability; Biological neural networks; Biological system modeling; Biology computing; Circuit faults; Circuit simulation; Hardware; Intelligent networks; Neural networks; Neurons; Polynomials;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.165601
Filename
165601
Link To Document