S-Map: A Network with a Simple Self-Organization Algorithm for Generative Topographic Mappings

Part of Advances in Neural Information Processing Systems 10 (NIPS 1997)

Authors

Kimmo Kiviluoto, Erkki Oja

Abstract

The S-Map is a network with a simple learning algorithm that com(cid:173) bines the self-organization capability of the Self-Organizing Map (SOM) and the probabilistic interpretability of the Generative To(cid:173) pographic Mapping (GTM). The simulations suggest that the S(cid:173) Map algorithm has a stronger tendency to self-organize from ran(cid:173) dom initial configuration than the GTM. The S-Map algorithm can be further simplified to employ pure Hebbian learning, with(cid:173) out changing the qualitative behaviour of the network.