Design of fault tolerant multilayer perceptronwith a desired level of robustness
Kwon, Bang · Electronics Letters · 1997
The definition of a fault tolerant neural network is presented. The definition makes it possible to design a network with a desired level of robustness. Based on this definition, an efficient method is proposed, called selective augmentation, which transforms a trained network into one that is fault tolerant against a stuck_at_0 fault at the hidden neurons. It is shown, through an example, that the resulting network designed by the proposed method is not only fault tolerant, but also much less redundant than a network designed by uniform augmentation.