Prediction error of a fault tolerant neural network

Prediction error is a powerful tool that measures the performance of a neural network. In this paper, we extend the technique to a kind of fault tolerant neural networks. Considering a neural network with multiple-node fault, we derive its generalized prediction error. Hence, the effective number of parameters of such a fault tolerant neural network is obtained. The difficulty in obtaining the mean prediction error is discussed. Finally, a simple procedure for estimation of the prediction error is empirically suggested.