A new method for fuzzy pattern classification based on measures of similarity

This paper presents a new method for fuzzy pattern classification. Its main difference from other methods is the introduction of a measure of similarity between the patterns and the point in the n-dimensional space which is to be classified. Furthermore this method is robust against noise corrupted patterns, which is an important aspect in many pattern classification problems.