Dynamic Self-Organising Maps: Theory, Methods and Applications
Arthur L Hsu, Isaam Saeed, Saman K Halgamuge
FOUNDATIONS OF COMPUTATIONAL INTELLIGENCE VOLUME 1: LEARNING APPROXIMATION | Studies in Computational Intelligence | SPRINGER | Published : 2009
In an effort to counter the restrictions enforced by the fixed map size and aspect ratio of a Kohonen Self-Organising Map, many variants to the method have been proposed. As a recent development, the Dynamic Self- Organising Map, also known as the Growing Self-Organising Map (GSOM), provides a balanced performance in topology preservation, data visualisation and computational speed. In this book chapter, a comprehensive description and theory of GSOM is provided, which also includes recent theoretical developments. Methods of clustering and identifying clusters using GSOM are also introduced here together with their related applications and results. © 2009 Springer-Verlag Berlin Heidelberg.