Neural network with ensembles

Pattern recognition systems usually have a relatively small number of patterns to be recognized. As a rule the number of handwritten symbols, number of phonemes or number of human faces are of the order of some dozens. But sometimes the pattern recognition task demands much more classes. For example, a continuous speech recognition system can be created on the base of syllables; a handwriting recognition system will be more efficient if the recognized units are not different letters, but triplets of letters. In these cases it is necessary to have various thousands of classes. In this paper we will consider the situation of the recognition problem that demands many thousands of classes to be recognized. For such problems we propose the use of the neural networks with ensembles. We give a short description of this type of neural network and calculate its storage capacity.