Abstract
To protect a feed-forward neural net against errors, error correcting codes have been used in previous studies to encode the output label. Here we analyze the effect of additive noise on the performance of a 1-layer coded net and compare it to an uncoded net. The derived results are then used to predict the performance of any multilayer neural net.