A Java simulation software for the study of the effects of the short-circuit faults in a feed forward neural network

Feed forward neural networks have an intrinsic fault tolerance to the faults of neurons from the hidden layer. In this paper is presented a simulation program that analyses the behaviour of a feed forward neural network, with a single hidden layer, in the presence of faults. The neural network is used to classify a binary image in four classes. The fault that is analysed is the short circuit of the output of one ore more neurons from the hidden layer. It is also analysed the influence of the dimension of the hidden layer (number of neurons) on the behaviour of the neural network in the presence of faults. For the training of the neural network it is used the backpropagation algorithm. The simulation program is written in the Java language.