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. >
['Piotr Berman', 'Ian Parberry', 'Georg Schnitger']
A note on the complexity of reliability in neural networks