A Neural Network Algorithm for Complex Pattern Classification Problems

This work presents an application of neural networks in pattern classification. A new algorithm for automatic classification of data is presented. That algorithm make use of a competitive neural network to aid the classification process. The algorithm gets a data set D and segment it into clusters. The only a priori information given is a number of auxiliary centers and a threshold distance. The algorithm uses the Mahalanobismetrics to cluster the data and find itself the number of classes.