Fast Automatic Configuration of Artificial Neural Networks Used for Binary Patterns Recognition

This paper presents a powerful method of an automatically generated architecture of neural networks used for binary pattems recognition, which can quickly and automatically reduce synapses in a way of minimally reducing a quality of recognition and a quality of generalization. Moreover, this method computes all weights in two runs over a leaming sequence, what makes this method very fast. First, the method calculates all binary features for each pattem and then weights are computed. Furthermore, there is a quality of generalization considered because it is one of the most important factors of recognition while using neural networks.