Bithreshold Neural Network Classifier

The fully connected 2-layer feedforward network architecture with the hidden layer consisting of bithreshold neurons is considered in the paper. We design the neural network multicategory classifier based on such an architecture. We also give the upper bound on the size of the bithreshold network, which is capable to recognize an arbitrary partition of the given finite set of patterns into a predefined number of classes. The learning algorithm is proposed for such neural networks. We give simulation results of the classifier performance on the real data set and discuss the influence of algorithm parameters on the quality of learning and the representational capacity of classifier.