Answers are grounded in this paper and cite their sources.
A means for analyzing the faulty behavior of neural networks is presented. Using an analogy between statistical physics and neural networks, a method for assessing the performance of a synchronous neural network model in the presence of faults is developed. Analytical predictions are computed using the statistical physics analogy and compared with the simulated behavior for two neuron models. An example of the analytical technique applied to an autoassociative memory is described.>
No takes yet. Share an insight, caveat, or question.
Belfore et al. (1991) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: