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
fDate :
11/1/1992 12:00:00 AM
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;
Journal_Title :
Neural Networks, IEEE Transactions on
