Abstract
In this paper, we propose the novel self-organizing map (SOM), in which the correlation between the elements in the input vector is considered. It is not considered that the unneccessary or redundant elements might be included in the input vector, and thus the distance between the input vector and the weight vectors can be an appropriate measure of distance. We propose the new self-organizing map algorithm, in which the distance between the input vector and the weight vectors are calculated considering correlation between the elements. The effectiveness and varidity of the proposed method is verified by applying it to classification of the facial profiles.
