A Study on An Improved Algorithm of Self-Adaptive Clustering Network
A study has been made on the algorithm of adaptive clustering network. The fact that different feature component has different function has not been considered in the algorithm of adaptive clustering network. The weight of every feature component has been considered in obtaining winning node and vigilance test of it. The weighted distance has been introduced for the patterns. An improved algorithm of adaptive clustering network has been proposed based on the above considerations. We have made experiments on Anderson's data and singular value features of ORL image base respectively. The experimental results show that both effectiveness and adaptiveness of the proposed algorithm has been improved